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2023, 36.
doi: 10.1186/s10033-023-00984-5
Abstract:
Microstructure and mechanical properties of GN9 Ferritic/Martensitic steel for sodium- cooled fast reactors have been investigated through orthogonal design and analysis. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), differential scanning calorimeter (DSC), tensile and impact tests were used to evaluate the heat treatment parameters on yield strength, elongation and ductile-to-brittle transition temperature (DBTT). The results indicate that the microstructures of GN9 steel after orthogonal heat treatments consist of tempered martensite, M23C6, MX carbides and MX carbonitrides. The average prior austenite grains increase and the lath width decreases with the austenitizing temperature increasing from 1000 ℃ to 1080 ℃. Tempering temperature is the most important factor that influences the dislocation evolution, yield strength and elongation compared with austenitizing temperature and cooling methods. Austenitizing temperature, tempering temperature and cooling methods show interactive effects on DBTT. Carbide morphology and distribution, which is influenced by austenitizing and tempering temperatures, is the critical microstructural factor that influences the Charpy impact energy and DBTT. Based on the orthogonal design and microstructural analysis, the optimal heat treatment of GN9 steel is austenitizing at 1000 ℃ for 0.5 h followed by air cooling and tempering at 760 ℃ for 1.5 h.
Microstructure and mechanical properties of GN9 Ferritic/Martensitic steel for sodium- cooled fast reactors have been investigated through orthogonal design and analysis. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), differential scanning calorimeter (DSC), tensile and impact tests were used to evaluate the heat treatment parameters on yield strength, elongation and ductile-to-brittle transition temperature (DBTT). The results indicate that the microstructures of GN9 steel after orthogonal heat treatments consist of tempered martensite, M23C6, MX carbides and MX carbonitrides. The average prior austenite grains increase and the lath width decreases with the austenitizing temperature increasing from 1000 ℃ to 1080 ℃. Tempering temperature is the most important factor that influences the dislocation evolution, yield strength and elongation compared with austenitizing temperature and cooling methods. Austenitizing temperature, tempering temperature and cooling methods show interactive effects on DBTT. Carbide morphology and distribution, which is influenced by austenitizing and tempering temperatures, is the critical microstructural factor that influences the Charpy impact energy and DBTT. Based on the orthogonal design and microstructural analysis, the optimal heat treatment of GN9 steel is austenitizing at 1000 ℃ for 0.5 h followed by air cooling and tempering at 760 ℃ for 1.5 h.
2023, 36.
doi: 10.1186/s10033-023-00950-1
Abstract:
The hardening on surface of complex profiles such as thread and spline manufactured by cold rolling can effectively improve the mechanical properties and surface quality of rolled parts. The distribution of hardness in superficial layer is closely related to the deformation by rolling. To establish the suitable correlation model for describing the relationship between strain and hardness during cold rolling forming process of complex profiles is helpful to the optimization of rolling parameters and improvement of rolling process. In this study, a physical analog experiment reflecting the uneven deformation during complex-profile rolling process has been extracted and designed, and then the large date set (more than 400 data points) of training samples reflecting the local deformation characteristics of complex-profile rolling have been obtained. Several types of polynomials and power functions were adopted in regression analysis, and the regression correlation models of 45# steel were evaluated by the single-pass and multi-pass physical analog experiments and the complex-profile rolling experiment. The results indicated that the predicting accuracy of polynomial regression model is better in the strain range (i.e.,\begin{document}$ \varepsilon \lt 1.2 $\end{document} \begin{document}$ \varepsilon \gt 1.2 $\end{document} \begin{document}$ \varepsilon \lt 1.2 $\end{document} \begin{document}$ \varepsilon \gt 1.2 $\end{document}
The hardening on surface of complex profiles such as thread and spline manufactured by cold rolling can effectively improve the mechanical properties and surface quality of rolled parts. The distribution of hardness in superficial layer is closely related to the deformation by rolling. To establish the suitable correlation model for describing the relationship between strain and hardness during cold rolling forming process of complex profiles is helpful to the optimization of rolling parameters and improvement of rolling process. In this study, a physical analog experiment reflecting the uneven deformation during complex-profile rolling process has been extracted and designed, and then the large date set (more than 400 data points) of training samples reflecting the local deformation characteristics of complex-profile rolling have been obtained. Several types of polynomials and power functions were adopted in regression analysis, and the regression correlation models of 45# steel were evaluated by the single-pass and multi-pass physical analog experiments and the complex-profile rolling experiment. The results indicated that the predicting accuracy of polynomial regression model is better in the strain range (i.e.,
2023, 36.
doi: 10.1186/s10033-023-00954-x
Abstract:
The forming limit diagram plays an important role in predicting the forming limit of sheet metals. Previous studies have shown that, the method to construct the forming limit diagram based on instability theory of the original shear failure criterion is effective and simple. The original shear instability criterion can accurately predict the left area of the forming limit diagram but not the right area. In this study, in order to improve the accuracy of the original shear failure criterion, a modified shear failure criterion was proposed based on in-depth analysis of the original shear failure criterion. The detailed improvement strategies of the shear failure criterion and the complete calculation process are given. Based on the modified shear failure criterion and different constitutive equations, the theoretical forming limit of TRIP780 steel and 5754O aluminum alloy sheet metals are calculated. By comparing the theoretical and experimental results, it is shown that proposed modified shear failure criterion can predict the right area of forming limit more reasonably than the original shear failure criterion. The effect of the pre-strain and constitutive equation on the forming limits are also analyzed in depth. The modified shear failure criterion proposed in this study provides an alternative and reliable method to predict forming limit of sheet metals.
The forming limit diagram plays an important role in predicting the forming limit of sheet metals. Previous studies have shown that, the method to construct the forming limit diagram based on instability theory of the original shear failure criterion is effective and simple. The original shear instability criterion can accurately predict the left area of the forming limit diagram but not the right area. In this study, in order to improve the accuracy of the original shear failure criterion, a modified shear failure criterion was proposed based on in-depth analysis of the original shear failure criterion. The detailed improvement strategies of the shear failure criterion and the complete calculation process are given. Based on the modified shear failure criterion and different constitutive equations, the theoretical forming limit of TRIP780 steel and 5754O aluminum alloy sheet metals are calculated. By comparing the theoretical and experimental results, it is shown that proposed modified shear failure criterion can predict the right area of forming limit more reasonably than the original shear failure criterion. The effect of the pre-strain and constitutive equation on the forming limits are also analyzed in depth. The modified shear failure criterion proposed in this study provides an alternative and reliable method to predict forming limit of sheet metals.
2023, 36.
doi: 10.1186/s10033-023-00942-1
Abstract:
To satisfy the requirements for the precise formation of large-scale high-performance lightweight components with inner ring reinforcement, a new multidirectional loading rotary extrusion forming technology is developed to match the linear motion with the rotary motion and actively increases the strong shear force. Its principle is that the radial force and rotating torque increase when the blank is axially extruded and loaded. Through the synergistic action of axial, radial, and rotating motions, the orderly flow of metal is controlled, and the cumulative severe plastic deformation (SPD) of an "uplift-trowel" micro-area is generated. Consequently, materials are uniformly strengthened and toughened. Simultaneously, through the continuous deformation of a punch "ellipse-circle, " a high reinforcement component is grown on the cylinder wall to achieve the high-quality formation of cylindrical parts or the inner-ring-reinforcement components. Additionally, the effective strain increases with rotation speed, and the maximum intensity on the basal plane decreases as the number of revolutions increase. The punch structure also affects the axial extrusion loading and equivalent plastic strain. Thus, the proposed technology enriches the plastic forming theory and widens the application field of plastic forming. Furthermore, the formed large-scale high-performance inner-ring-stiffened magnesium components have been successfully verified in aerospace equipment, thereby solving the problems of integral forming and severe deformation strengthening and toughening. The developed technology has good prospects for mass production and application.
To satisfy the requirements for the precise formation of large-scale high-performance lightweight components with inner ring reinforcement, a new multidirectional loading rotary extrusion forming technology is developed to match the linear motion with the rotary motion and actively increases the strong shear force. Its principle is that the radial force and rotating torque increase when the blank is axially extruded and loaded. Through the synergistic action of axial, radial, and rotating motions, the orderly flow of metal is controlled, and the cumulative severe plastic deformation (SPD) of an "uplift-trowel" micro-area is generated. Consequently, materials are uniformly strengthened and toughened. Simultaneously, through the continuous deformation of a punch "ellipse-circle, " a high reinforcement component is grown on the cylinder wall to achieve the high-quality formation of cylindrical parts or the inner-ring-reinforcement components. Additionally, the effective strain increases with rotation speed, and the maximum intensity on the basal plane decreases as the number of revolutions increase. The punch structure also affects the axial extrusion loading and equivalent plastic strain. Thus, the proposed technology enriches the plastic forming theory and widens the application field of plastic forming. Furthermore, the formed large-scale high-performance inner-ring-stiffened magnesium components have been successfully verified in aerospace equipment, thereby solving the problems of integral forming and severe deformation strengthening and toughening. The developed technology has good prospects for mass production and application.
2023, 36.
doi: 10.1186/s10033-023-00919-0
Abstract:
Bridge steel has been widely used in recent years for its excellent performance. Understanding the high-temperature Dynamic Recrystallization (DRX) behavior of high-performance bridge steel plays an important role in guiding the thermomechanical processing process. In the present study, the hot deformation behavior of Q370qE bridge steel was investigated by hot compression tests conducted on a Gleeble 3800-GTC thermal-mechanical physical simulation system at temperatures ranging from 900 ℃ to 1100 ℃ and strain rates ranging from 0.01 s−1 to 10 s−1. The obtained results were used to plot the true stress-strain and work-hardening rate curves of the experimental steel, with the latter curves used to determine the critical strains for the initiation of DRX. The Zener-Hollomon equation was subsequently applied to establish the correspondence between temperature and strain rate during the high-temperature plastic deformation of bridge steel. In terms of the DRX volume fraction solution, a new method for establishing DRX volume fraction was proposed based on two theoretical models. The good weathering and corrosion resistance of bridge steel lead to difficulties in microstructure etching. To solve this, the MTEX technology was used to further develop EBSD data to characterize the original microstructure of Q370qE bridge steel. This paper lays the theoretical foundation for studying the DRX behavior of Q370qE bridge steel.
Bridge steel has been widely used in recent years for its excellent performance. Understanding the high-temperature Dynamic Recrystallization (DRX) behavior of high-performance bridge steel plays an important role in guiding the thermomechanical processing process. In the present study, the hot deformation behavior of Q370qE bridge steel was investigated by hot compression tests conducted on a Gleeble 3800-GTC thermal-mechanical physical simulation system at temperatures ranging from 900 ℃ to 1100 ℃ and strain rates ranging from 0.01 s−1 to 10 s−1. The obtained results were used to plot the true stress-strain and work-hardening rate curves of the experimental steel, with the latter curves used to determine the critical strains for the initiation of DRX. The Zener-Hollomon equation was subsequently applied to establish the correspondence between temperature and strain rate during the high-temperature plastic deformation of bridge steel. In terms of the DRX volume fraction solution, a new method for establishing DRX volume fraction was proposed based on two theoretical models. The good weathering and corrosion resistance of bridge steel lead to difficulties in microstructure etching. To solve this, the MTEX technology was used to further develop EBSD data to characterize the original microstructure of Q370qE bridge steel. This paper lays the theoretical foundation for studying the DRX behavior of Q370qE bridge steel.
2023, 36.
doi: 10.1186/s10033-023-00959-6
Abstract:
Graphene as a lubricating additive holds great potential for industrial lubrication. However, its poor dispersity and compatibility with base oils and grease hinder maximizing performance. Here, the influence of graphene dispersion on the thickening effect and lubrication function is considered. A well-dispersed lubricant additive was obtained via trihexyl tetradecyl phosphonium bis(2-ethylhexyl) phosphate modified graphene ([P66614][DEHP]-G). Then lithium complex grease was prepared by saponification with 12-OH stearic acid, sebacic acid, and lithium hydroxide, using polyalphaolefin (PAO20) as base oil and the modified-graphene as lubricating additive, with the original graphene as a comparison. The physicochemical properties and lubrication performance of the as-prepared greases were evaluated in detail. The results show that the as-prepared greases have high dropping point and colloidal stability. Furthermore, modified-graphene lithium complex grease offered the best friction reduction and anti-wear abilities, manifesting the reduction of friction coefficient and wear volume up to 18.84% and 67.34%, respectively. With base oil overflow and afflux, well-dispersed [P66614][DEHP]-G was readily adsorbed to the worn surfaces, resulting in the formation of a continuous and dense graphene deposition film. The synergy of deposited graphene-film, spilled oil, and adhesive grease greatly improves the lubrication function of grease. This research paves the way for modulating high-performance lithium complex grease to reduce the friction and wear of movable machinery.
Graphene as a lubricating additive holds great potential for industrial lubrication. However, its poor dispersity and compatibility with base oils and grease hinder maximizing performance. Here, the influence of graphene dispersion on the thickening effect and lubrication function is considered. A well-dispersed lubricant additive was obtained via trihexyl tetradecyl phosphonium bis(2-ethylhexyl) phosphate modified graphene ([P66614][DEHP]-G). Then lithium complex grease was prepared by saponification with 12-OH stearic acid, sebacic acid, and lithium hydroxide, using polyalphaolefin (PAO20) as base oil and the modified-graphene as lubricating additive, with the original graphene as a comparison. The physicochemical properties and lubrication performance of the as-prepared greases were evaluated in detail. The results show that the as-prepared greases have high dropping point and colloidal stability. Furthermore, modified-graphene lithium complex grease offered the best friction reduction and anti-wear abilities, manifesting the reduction of friction coefficient and wear volume up to 18.84% and 67.34%, respectively. With base oil overflow and afflux, well-dispersed [P66614][DEHP]-G was readily adsorbed to the worn surfaces, resulting in the formation of a continuous and dense graphene deposition film. The synergy of deposited graphene-film, spilled oil, and adhesive grease greatly improves the lubrication function of grease. This research paves the way for modulating high-performance lithium complex grease to reduce the friction and wear of movable machinery.
2023, 36: 67.
doi: 10.1186/s10033-023-00892-8
Abstract:
Solar arrays are the primary energy source for spacecraft. Although traditional rigid solar arrays improve power supply, the quality increases proportionally. Hence, it is difficult to satisfy the requirements of high-power and low-cost space applications. In this study, a shape-memory polymer composite (SMPC) boom was designed, fabricated, and characterized for flexible reel-type solar arrays. The SMPC boom was fabricated from a smart material, a shape-memory polymer composite, whose mechanical properties were tested. Additionally, a mathematical model of the bending stiffness of the SMPC boom was developed, and the bending and buckling behaviors of the boom were further analyzed using the ABAQUS software. An SMPC boom was fabricated to demonstrate its shape memory characteristics, and the driving force of the booms with varying geometric parameters was investigated. We also designed and manufactured a reel-type solar array based on an SMPC boom and verified its self-deployment capability. The results indicated that the SMPC boom can be used as a deployable unit to roll out flexible solar arrays.
Solar arrays are the primary energy source for spacecraft. Although traditional rigid solar arrays improve power supply, the quality increases proportionally. Hence, it is difficult to satisfy the requirements of high-power and low-cost space applications. In this study, a shape-memory polymer composite (SMPC) boom was designed, fabricated, and characterized for flexible reel-type solar arrays. The SMPC boom was fabricated from a smart material, a shape-memory polymer composite, whose mechanical properties were tested. Additionally, a mathematical model of the bending stiffness of the SMPC boom was developed, and the bending and buckling behaviors of the boom were further analyzed using the ABAQUS software. An SMPC boom was fabricated to demonstrate its shape memory characteristics, and the driving force of the booms with varying geometric parameters was investigated. We also designed and manufactured a reel-type solar array based on an SMPC boom and verified its self-deployment capability. The results indicated that the SMPC boom can be used as a deployable unit to roll out flexible solar arrays.
2023, 36: 72.
doi: 10.1186/s10033-023-00901-w
Abstract:
Magnesium (Mg) alloys are the lightest metal structural material for engineering applications and therefore have a wide market of applications. However, compared to steel and aluminum alloys, Mg alloys have lower mechanical properties, which greatly limits their application. Extrusion is one of the most important processing methods for Mg and its alloys. However, the effect of such a heterogeneous microstructure achieved at low temperatures on the mechanical properties is lacking investigation. In this work, commercial AZ80 alloys with different initial microstructures (as-cast and as-homogenized) were selected and extruded at a low extrusion temperature of 220 ℃ and a low extrusion ratio of 4. The microstructure and mechanical properties of the two extruded AZ80 alloys were investigated. The results show that homogenized-extruded (HE) sample exhibits higher strength than the cast-extruded (CE) sample, which is mainly attributed to the high number density of fine dynamic precipitates and the high fraction of recrystallized ultrafine grains. Compared to the coarse compounds existing in CE sample, the fine dynamical precipitates of Mg17(Al, Zn)12 form in the HE sample can effectively promote the dynamical recrystallization during extrusion, while they exhibit a similar effect on the size and orientation of the recrystallized grains. These results can facilitate the designing of high-strength wrought magnesium alloys by rational microstructure construction.
Magnesium (Mg) alloys are the lightest metal structural material for engineering applications and therefore have a wide market of applications. However, compared to steel and aluminum alloys, Mg alloys have lower mechanical properties, which greatly limits their application. Extrusion is one of the most important processing methods for Mg and its alloys. However, the effect of such a heterogeneous microstructure achieved at low temperatures on the mechanical properties is lacking investigation. In this work, commercial AZ80 alloys with different initial microstructures (as-cast and as-homogenized) were selected and extruded at a low extrusion temperature of 220 ℃ and a low extrusion ratio of 4. The microstructure and mechanical properties of the two extruded AZ80 alloys were investigated. The results show that homogenized-extruded (HE) sample exhibits higher strength than the cast-extruded (CE) sample, which is mainly attributed to the high number density of fine dynamic precipitates and the high fraction of recrystallized ultrafine grains. Compared to the coarse compounds existing in CE sample, the fine dynamical precipitates of Mg17(Al, Zn)12 form in the HE sample can effectively promote the dynamical recrystallization during extrusion, while they exhibit a similar effect on the size and orientation of the recrystallized grains. These results can facilitate the designing of high-strength wrought magnesium alloys by rational microstructure construction.
2023, 36: 89.
doi: 10.1186/s10033-023-00925-2
Abstract:
As the first safety barrier of nuclear reactors, zirconium alloy cladding tubes have attracted extensive attention because of its good mechanical properties. The strength and ductility of zirconium alloy are of great significance to the service process of cladding tubes, while brittle hydrides precipitate and thus deteriorate the overall performance. Based on the cohesive finite element method, the effects of cohesive strength, interfacial characteristics, and hydrides geometric characteristics on the strength and ductility of two-phase material (zirconium alloy with hydrides) are numerically simulated. The results show that the fracture behavior is significantly affected by the cohesive strength and that the overall strength and ductility are sensitive to the cohesive strength of the zirconium alloy. Furthermore, the interface is revealed to have prominent effects on the overall fracture behavior. When the cohesive strength and fracture energy of the interface are higher than those of the hydride phase, fracture initiates in the hydrides, which is consistent with the experimental phenomena. In addition, it is found that the number density and arrangement of hydrides play important roles in the overall strength and ductility. Our simulation provides theoretical support for the performance analysis of hydrogenated zirconium alloys during nuclear reactor operation.
As the first safety barrier of nuclear reactors, zirconium alloy cladding tubes have attracted extensive attention because of its good mechanical properties. The strength and ductility of zirconium alloy are of great significance to the service process of cladding tubes, while brittle hydrides precipitate and thus deteriorate the overall performance. Based on the cohesive finite element method, the effects of cohesive strength, interfacial characteristics, and hydrides geometric characteristics on the strength and ductility of two-phase material (zirconium alloy with hydrides) are numerically simulated. The results show that the fracture behavior is significantly affected by the cohesive strength and that the overall strength and ductility are sensitive to the cohesive strength of the zirconium alloy. Furthermore, the interface is revealed to have prominent effects on the overall fracture behavior. When the cohesive strength and fracture energy of the interface are higher than those of the hydride phase, fracture initiates in the hydrides, which is consistent with the experimental phenomena. In addition, it is found that the number density and arrangement of hydrides play important roles in the overall strength and ductility. Our simulation provides theoretical support for the performance analysis of hydrogenated zirconium alloys during nuclear reactor operation.
2023, 36: 95.
doi: 10.1186/s10033-023-00921-6
Abstract:
The crystal plasticity finite element method (CPFEM) is widely used to explore the microscopic mechanical behavior of materials and understand the deformation mechanism at the grain-level. However, few CPFEM simulation studies have been carried out to analyze the nanoindentation deformation mechanism of polycrystalline materials at the microscale level. In this study, a three-dimensional CPFEM-based nanoindentation simulation is performed on an Inconel 718 polycrystalline material to examine the influence of different crystallographic parameters on nanoindentation behavior. A representative volume element model is developed to calibrate the crystal plastic constitutive parameters by comparing the stress-strain data with the experimental results. The indentation force-displacement curves, stress distributions, and pile-up patterns are obtained by CPFEM simulation. The results show that the crystallographic orientation and grain boundary have little influence on the force-displacement curves of the nanoindentation, but significantly influence the local stress distributions and shape of the pile-up patterns. As the difference in crystallographic orientation between grains increases, changes in the pile-up patterns and stress distributions caused by this effect become more significant. In addition, the simulation results reveal that the existence of grain boundaries affects the continuity of the stress distribution. The obstruction on the continuity of stress distribution increases as the grain boundary angle increases. This research demonstrates that the proposed CPFEM model can well describe the microscopic compressive deformation behaviors of Inconel 718 under nanoindentation.
The crystal plasticity finite element method (CPFEM) is widely used to explore the microscopic mechanical behavior of materials and understand the deformation mechanism at the grain-level. However, few CPFEM simulation studies have been carried out to analyze the nanoindentation deformation mechanism of polycrystalline materials at the microscale level. In this study, a three-dimensional CPFEM-based nanoindentation simulation is performed on an Inconel 718 polycrystalline material to examine the influence of different crystallographic parameters on nanoindentation behavior. A representative volume element model is developed to calibrate the crystal plastic constitutive parameters by comparing the stress-strain data with the experimental results. The indentation force-displacement curves, stress distributions, and pile-up patterns are obtained by CPFEM simulation. The results show that the crystallographic orientation and grain boundary have little influence on the force-displacement curves of the nanoindentation, but significantly influence the local stress distributions and shape of the pile-up patterns. As the difference in crystallographic orientation between grains increases, changes in the pile-up patterns and stress distributions caused by this effect become more significant. In addition, the simulation results reveal that the existence of grain boundaries affects the continuity of the stress distribution. The obstruction on the continuity of stress distribution increases as the grain boundary angle increases. This research demonstrates that the proposed CPFEM model can well describe the microscopic compressive deformation behaviors of Inconel 718 under nanoindentation.
2023, 36: 104.
doi: 10.1186/s10033-023-00898-2
Abstract:
With the deepening of human research on deep space exploration, our research on the soft landing methods of landers has gradually deepened. Adding a buffer and energy-absorbing structure to the leg structure of the lander has become an effective design solution. Based on the energy-absorbing structure of the leg of the interstellar lander, this paper studies the appearance characteristics of the predatory feet of the Odontodactylus scyllarus. The predatory feet of the Odontodactylus scyllarus can not only hit the prey highly when preying, but also can easily withstand the huge counter-impact force. The predatory feet structure of the Odontodactylus scyllarus, like a symmetrical cone, shows excellent rigidity and energy absorption capacity. Inspired by this discovery, we used SLM technology to design and manufacture two nickel-titanium samples, which respectively show high elasticity, shape memory, and get better energy absorption capacity. This research provides an effective way to design and manufacture high-mechanical energy-absorbing buffer structures using bionic 3D printing technology and nickel-titanium alloys.
With the deepening of human research on deep space exploration, our research on the soft landing methods of landers has gradually deepened. Adding a buffer and energy-absorbing structure to the leg structure of the lander has become an effective design solution. Based on the energy-absorbing structure of the leg of the interstellar lander, this paper studies the appearance characteristics of the predatory feet of the Odontodactylus scyllarus. The predatory feet of the Odontodactylus scyllarus can not only hit the prey highly when preying, but also can easily withstand the huge counter-impact force. The predatory feet structure of the Odontodactylus scyllarus, like a symmetrical cone, shows excellent rigidity and energy absorption capacity. Inspired by this discovery, we used SLM technology to design and manufacture two nickel-titanium samples, which respectively show high elasticity, shape memory, and get better energy absorption capacity. This research provides an effective way to design and manufacture high-mechanical energy-absorbing buffer structures using bionic 3D printing technology and nickel-titanium alloys.
2023, 36.
doi: 10.1186/s10033-023-00943-0
Abstract:
Additive manufacturing (AM) technology such as selective laser melting (SLM) often produces a high reflection phenomenon that makes defect detection and information extraction challenging. Meanwhile, it is essential to establish a characterization method for defect analysis to provide sufficient information for process diagnosis and optimization. However, there is still a lack of universal standards for the characterization of defects in SLM parts. In this study, a polarization-based imaging system was proposed, and a set of characterization parameters for SLM defects was established. The contrast, defect contour information, and high reflection suppression effect of the SLM part defects were analyzed. Comparative analysis was conducted on defect characterization parameters, including geometric and texture parameters. The experimental results demonstrated the effects of the polarization imaging system and verified the feasibility of the defect feature extraction and characterization method. The research work provides an effective solution for defect detection and helps to establish a universal standard for defect characterization in additive manufacturing.
Additive manufacturing (AM) technology such as selective laser melting (SLM) often produces a high reflection phenomenon that makes defect detection and information extraction challenging. Meanwhile, it is essential to establish a characterization method for defect analysis to provide sufficient information for process diagnosis and optimization. However, there is still a lack of universal standards for the characterization of defects in SLM parts. In this study, a polarization-based imaging system was proposed, and a set of characterization parameters for SLM defects was established. The contrast, defect contour information, and high reflection suppression effect of the SLM part defects were analyzed. Comparative analysis was conducted on defect characterization parameters, including geometric and texture parameters. The experimental results demonstrated the effects of the polarization imaging system and verified the feasibility of the defect feature extraction and characterization method. The research work provides an effective solution for defect detection and helps to establish a universal standard for defect characterization in additive manufacturing.
2023, 36.
doi: 10.1186/s10033-023-00965-8
Abstract:
In recent years, as a promising way to realize digital transformation, digital twin shop-floor (DTS) plays an important role in smart manufacturing. The core feature of DTS is the synchronization. How to implement and maintain the synchronization is critical for DTS. However, there is still a lack of a common definition for synchronization in DTS. Besides, a systematic synchronization mechanism for DTS is strongly needed. This paper first summarizes the definition and requirements of synchronization in DTS, to clarify the understanding of synchronization in DTS. Then, a 5M synchronization mechanism for DTS is proposed, where 5M refers to multi-system data, multi-fidelity model, multi-resource state, multi-level state, and multi-stage operation. As a bottom-up synchronization mechanism, 5M synchronization mechanism for DTS has the potential to support DTS to achieve and maintain physical-virtual state synchronization, and to realize operation synchronization of DTS. The implementation methods of 5M synchronization mechanism for DTS are also introduced. Finally, the proposed synchronization mechanism is validated in a digital twin satellite assembly shop-floor, which proves the effectiveness and feasibility of the mechanism.
In recent years, as a promising way to realize digital transformation, digital twin shop-floor (DTS) plays an important role in smart manufacturing. The core feature of DTS is the synchronization. How to implement and maintain the synchronization is critical for DTS. However, there is still a lack of a common definition for synchronization in DTS. Besides, a systematic synchronization mechanism for DTS is strongly needed. This paper first summarizes the definition and requirements of synchronization in DTS, to clarify the understanding of synchronization in DTS. Then, a 5M synchronization mechanism for DTS is proposed, where 5M refers to multi-system data, multi-fidelity model, multi-resource state, multi-level state, and multi-stage operation. As a bottom-up synchronization mechanism, 5M synchronization mechanism for DTS has the potential to support DTS to achieve and maintain physical-virtual state synchronization, and to realize operation synchronization of DTS. The implementation methods of 5M synchronization mechanism for DTS are also introduced. Finally, the proposed synchronization mechanism is validated in a digital twin satellite assembly shop-floor, which proves the effectiveness and feasibility of the mechanism.
2023, 36.
doi: 10.1186/s10033-023-00955-w
Abstract:
The service cycle and dynamic performance of structural parts are affected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground offline, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was first set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were configured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize real-time communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profile model of the base material in the weld area using a polynomial fitting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verified the effectiveness of the system's correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verified through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction effect and high robustness.
The service cycle and dynamic performance of structural parts are affected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground offline, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was first set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were configured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize real-time communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profile model of the base material in the weld area using a polynomial fitting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verified the effectiveness of the system's correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verified through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction effect and high robustness.
2023, 36.
doi: 10.1186/s10033-023-00932-3
Abstract:
Shield machines are currently the main tool for underground tunnel construction. Due to the complexity and variability of the underground construction environment, it is necessary to accurately identify the ground in real-time during the tunnel construction process to match and adjust the tunnel parameters according to the geological conditions to ensure construction safety. Compared with the traditional method of stratum identification based on staged drilling sampling, the real-time stratum identification method based on construction data has the advantages of low cost and high precision. Due to the huge amount of sensor data of the ultra-large diameter mud-water balance shield machine, in order to balance the identification time and recognition accuracy of the formation, it is necessary to screen the multivariate data features collected by hundreds of sensors. In response to this problem, this paper proposes a voting-based feature extraction method (VFS), which integrates multiple feature extraction algorithms FSM, and the frequency of each feature in all feature extraction algorithms is the basis for voting. At the same time, in order to verify the wide applicability of the method, several commonly used classification models are used to train and test the obtained effective feature data, and the model accuracy and recognition time are used as evaluation indicators, and the classification with the best combination with VFS is obtained. The experimental results of shield machine data of 6 different geological structures show that the average accuracy of 13 features obtained by VFS combined with different classification algorithms is 91%; among them, the random forest model takes less time and has the highest recognition accuracy, reaching 93%, showing best compatibility with VFS. Therefore, the VFS algorithm proposed in this paper has high reliability and wide applicability for stratum identification in the process of tunnel construction, and can be matched with a variety of classifier algorithms. By combining 13 features selected from shield machine data features with random forest, the identification of the construction stratum environment of shield tunnels can be well realized, and further theoretical guidance for underground engineering construction can be provided.
Shield machines are currently the main tool for underground tunnel construction. Due to the complexity and variability of the underground construction environment, it is necessary to accurately identify the ground in real-time during the tunnel construction process to match and adjust the tunnel parameters according to the geological conditions to ensure construction safety. Compared with the traditional method of stratum identification based on staged drilling sampling, the real-time stratum identification method based on construction data has the advantages of low cost and high precision. Due to the huge amount of sensor data of the ultra-large diameter mud-water balance shield machine, in order to balance the identification time and recognition accuracy of the formation, it is necessary to screen the multivariate data features collected by hundreds of sensors. In response to this problem, this paper proposes a voting-based feature extraction method (VFS), which integrates multiple feature extraction algorithms FSM, and the frequency of each feature in all feature extraction algorithms is the basis for voting. At the same time, in order to verify the wide applicability of the method, several commonly used classification models are used to train and test the obtained effective feature data, and the model accuracy and recognition time are used as evaluation indicators, and the classification with the best combination with VFS is obtained. The experimental results of shield machine data of 6 different geological structures show that the average accuracy of 13 features obtained by VFS combined with different classification algorithms is 91%; among them, the random forest model takes less time and has the highest recognition accuracy, reaching 93%, showing best compatibility with VFS. Therefore, the VFS algorithm proposed in this paper has high reliability and wide applicability for stratum identification in the process of tunnel construction, and can be matched with a variety of classifier algorithms. By combining 13 features selected from shield machine data features with random forest, the identification of the construction stratum environment of shield tunnels can be well realized, and further theoretical guidance for underground engineering construction can be provided.
2023, 36.
doi: 10.1186/s10033-023-00973-8
Abstract:
Shell-infill structures comprise an exterior solid shell and an interior lattice infill, whose closed features yield superior comprehensive mechanical performance and light weight. Additive manufacturing (AM) can ensure the fabrication of complex structures. Although the mechanical behaviors of lattice structures have been extensively studied, the corresponding mechanical performances of integrated-manufactured shell structures with lattice infills should be systematically investigated due to the coupling effect of the exterior shell and lattice infill. This study investigated the mechanical properties and energy absorption of AlSi10Mg shell structures with a body-centered cubic lattice infill fabricated by AM. Quasi-static compressive experiments and corresponding finite element analysis were conducted to investigate the mechanical behavior. In addition, two different finite element modeling methods were compared to determine the appropriate modeling strategy in terms of deformation behavior. A study of different parameters, including lattice diameters and shell thicknesses, was conducted to identify their effect on mechanical performance. The results demonstrate the mechanical advantages of shell-infill structures, in which the exterior shell strengthens the lattice infill by up to 2.3 times in terms of the effective Young's modulus. Increasing the infill strut diameter can improve the specific energy absorption by up to 1.6 times.
Shell-infill structures comprise an exterior solid shell and an interior lattice infill, whose closed features yield superior comprehensive mechanical performance and light weight. Additive manufacturing (AM) can ensure the fabrication of complex structures. Although the mechanical behaviors of lattice structures have been extensively studied, the corresponding mechanical performances of integrated-manufactured shell structures with lattice infills should be systematically investigated due to the coupling effect of the exterior shell and lattice infill. This study investigated the mechanical properties and energy absorption of AlSi10Mg shell structures with a body-centered cubic lattice infill fabricated by AM. Quasi-static compressive experiments and corresponding finite element analysis were conducted to investigate the mechanical behavior. In addition, two different finite element modeling methods were compared to determine the appropriate modeling strategy in terms of deformation behavior. A study of different parameters, including lattice diameters and shell thicknesses, was conducted to identify their effect on mechanical performance. The results demonstrate the mechanical advantages of shell-infill structures, in which the exterior shell strengthens the lattice infill by up to 2.3 times in terms of the effective Young's modulus. Increasing the infill strut diameter can improve the specific energy absorption by up to 1.6 times.
2023, 36.
doi: 10.1186/s10033-023-00964-9
Abstract:
The equipment used in various fields contains an increasing number of parts with curved surfaces of increasing size. Five-axis computer numerical control (CNC) milling is the main parts machining method, while dynamics analysis has always been a research hotspot. The cutting conditions determined by the cutter axis, tool path, and workpiece geometry are complex and changeable, which has made dynamics research a major challenge. For this reason, this paper introduces the innovative idea of applying dimension reduction and mapping to the five-axis machining of curved surfaces, and proposes an efficient dynamics analysis model. To simplify the research object, the cutter position points along the tool path were discretized into inclined plane five-axis machining. The cutter dip angle and feed deflection angle were used to define the spatial position relationship in five-axis machining. These were then taken as the new base variables to construct an abstract two-dimensional space and establish the mapping relationship between the cutter position point and space point sets to further simplify the dimensions of the research object. Based on the in-cut cutting edge solved by the space limitation method, the dynamics of the inclined plane five-axis machining unit were studied, and the results were uniformly stored in the abstract space to produce a database. Finally, the prediction of the milling force and vibration state along the tool path became a data extraction process that significantly improved efficiency. Two experiments were also conducted which proved the accuracy and efficiency of the proposed dynamics analysis model. This study has great potential for the online synchronization of intelligent machining of large surfaces.
The equipment used in various fields contains an increasing number of parts with curved surfaces of increasing size. Five-axis computer numerical control (CNC) milling is the main parts machining method, while dynamics analysis has always been a research hotspot. The cutting conditions determined by the cutter axis, tool path, and workpiece geometry are complex and changeable, which has made dynamics research a major challenge. For this reason, this paper introduces the innovative idea of applying dimension reduction and mapping to the five-axis machining of curved surfaces, and proposes an efficient dynamics analysis model. To simplify the research object, the cutter position points along the tool path were discretized into inclined plane five-axis machining. The cutter dip angle and feed deflection angle were used to define the spatial position relationship in five-axis machining. These were then taken as the new base variables to construct an abstract two-dimensional space and establish the mapping relationship between the cutter position point and space point sets to further simplify the dimensions of the research object. Based on the in-cut cutting edge solved by the space limitation method, the dynamics of the inclined plane five-axis machining unit were studied, and the results were uniformly stored in the abstract space to produce a database. Finally, the prediction of the milling force and vibration state along the tool path became a data extraction process that significantly improved efficiency. Two experiments were also conducted which proved the accuracy and efficiency of the proposed dynamics analysis model. This study has great potential for the online synchronization of intelligent machining of large surfaces.
2023, 36.
doi: 10.1186/s10033-023-00935-0
Abstract:
Three-dimensional (3D) printing technology is expected to solve the organ shortage problem. However, owing to the accuracy limitations, it is difficult for the current bioprinting technology to achieve an accurate control of the spatial position and distribution of a single cell or single component droplet. In this study, to accurately achieve the directional deposition of different cells and biological materials in the spatial position for the construction of large transplantable tissues and organs, a high-precision multichannel 3D bioprinter with submicron-level motion accuracy is designed, and concurrent and synergistic printing methods are proposed. Based on the high-precision motion characteristics of the gantry structure and the requirements of concurrent and synergistic printing, a 3D bioprinting system with a set of 6 channels is designed to achieve six-in-one printing. Based on the Visual C++ environment, a control system software that integrates the programmable multi-axis controller (PMAC) motion, pneumatic, and temperature control subsystems was developed and designed. Finally, based on measurements and experiments, the 3D bioprinter and its control system was verified to fulfil the requirements of multichannel, concurrent, and synergistic printing with submicron-level motion accuracy, significantly shortening the printing time and improving the printing efficiency. This study not only provides an equipment basis for printing complex heterogeneous tissue structures, but also improves the flexibility and functionality of bioprinting, and ultimately makes the construction of complex multicellular tissues or organs possible.
Three-dimensional (3D) printing technology is expected to solve the organ shortage problem. However, owing to the accuracy limitations, it is difficult for the current bioprinting technology to achieve an accurate control of the spatial position and distribution of a single cell or single component droplet. In this study, to accurately achieve the directional deposition of different cells and biological materials in the spatial position for the construction of large transplantable tissues and organs, a high-precision multichannel 3D bioprinter with submicron-level motion accuracy is designed, and concurrent and synergistic printing methods are proposed. Based on the high-precision motion characteristics of the gantry structure and the requirements of concurrent and synergistic printing, a 3D bioprinting system with a set of 6 channels is designed to achieve six-in-one printing. Based on the Visual C++ environment, a control system software that integrates the programmable multi-axis controller (PMAC) motion, pneumatic, and temperature control subsystems was developed and designed. Finally, based on measurements and experiments, the 3D bioprinter and its control system was verified to fulfil the requirements of multichannel, concurrent, and synergistic printing with submicron-level motion accuracy, significantly shortening the printing time and improving the printing efficiency. This study not only provides an equipment basis for printing complex heterogeneous tissue structures, but also improves the flexibility and functionality of bioprinting, and ultimately makes the construction of complex multicellular tissues or organs possible.
2023, 36.
doi: 10.1186/s10033-023-00981-8
Abstract:
Mechanical agitation in baffled vessels with turbines plays a vital role in achieving homogeneous fluid mixing and promoting various transfer operations. Therefore, designing vessels with optimal energy efficiency and flow dynamics is essential to enhance operational performance and eliminate flow perturbations. Hence, the present research focuses on a numerical investigation of the impact of inclined slots with different angles installed at the sidewall of a cylindrical vessel equipped with a Rushton turbine. This study explores power consumption and vortex size while considering various rotation directions of the impeller with different rotation speeds. The numerical simulations are conducted for Reynolds numbers ranging from 104 to 105, using the RANS k-ε turbulence model to govern the flow inside the stirred vessel, accounting for mass and momentum balances. The results have shown that the installation of slots reduces power consumption and vortex size compared to conventional vessel configurations. Moreover, increasing the slot angle from 0 to 32.5° further reduces energy consumption and vortex size, especially with negative rotation speeds. On the other hand, increasing the Reynolds numbers leads to a decrease in power consumption and an increase in vortex size. The present research therefore proposes a design for constructing Rushton-turbine stirred vessels offering optimal operation, characterized by reduced energy consumption and minimized vortex size.
Mechanical agitation in baffled vessels with turbines plays a vital role in achieving homogeneous fluid mixing and promoting various transfer operations. Therefore, designing vessels with optimal energy efficiency and flow dynamics is essential to enhance operational performance and eliminate flow perturbations. Hence, the present research focuses on a numerical investigation of the impact of inclined slots with different angles installed at the sidewall of a cylindrical vessel equipped with a Rushton turbine. This study explores power consumption and vortex size while considering various rotation directions of the impeller with different rotation speeds. The numerical simulations are conducted for Reynolds numbers ranging from 104 to 105, using the RANS k-ε turbulence model to govern the flow inside the stirred vessel, accounting for mass and momentum balances. The results have shown that the installation of slots reduces power consumption and vortex size compared to conventional vessel configurations. Moreover, increasing the slot angle from 0 to 32.5° further reduces energy consumption and vortex size, especially with negative rotation speeds. On the other hand, increasing the Reynolds numbers leads to a decrease in power consumption and an increase in vortex size. The present research therefore proposes a design for constructing Rushton-turbine stirred vessels offering optimal operation, characterized by reduced energy consumption and minimized vortex size.
2023, 36.
doi: 10.1186/s10033-023-00982-7
Abstract:
The application of continuous natural fibers as reinforcement in composite thin-walled structures offers a feasible approach to achieve light weight and high strength while remaining environmentally friendly. In addition, additive manufacturing technology provides a favorable process foundation for its realization. In this study, the printability and energy absorption properties of 3D printed continuous fiber reinforced thin-walled structures with different configurations were investigated. The results suggested that a low printing speed and a proper layer thickness would mitigate the printing defects within the structures. The printing geometry accuracy of the structures could be further improved by rounding the sharp corners with appropriate radii. This study successfully fabricated structures with various configurations characterized by high geometric accuracy through printing parameters optimization and path smoothing. Moreover, the compressive property and energy absorption characteristics of the structures under quasi-static axial compression were evaluated and compared. It was found that all studied thin-walled structures exhibited progressive folding deformation patterns during compression. In particular, energy absorption process was achieved through the combined damage modes of plastic deformation, fiber pullout and delamination. Furthermore, the comparison results showed that the hexagonal structure exhibited the best energy absorption performance. The study revealed the structure-mechanical property relationship of 3D printed continuous fiber reinforced composite thin-walled structures through the analysis of multiscale failure characteristics and load response, which is valuable for broadening their applications.
The application of continuous natural fibers as reinforcement in composite thin-walled structures offers a feasible approach to achieve light weight and high strength while remaining environmentally friendly. In addition, additive manufacturing technology provides a favorable process foundation for its realization. In this study, the printability and energy absorption properties of 3D printed continuous fiber reinforced thin-walled structures with different configurations were investigated. The results suggested that a low printing speed and a proper layer thickness would mitigate the printing defects within the structures. The printing geometry accuracy of the structures could be further improved by rounding the sharp corners with appropriate radii. This study successfully fabricated structures with various configurations characterized by high geometric accuracy through printing parameters optimization and path smoothing. Moreover, the compressive property and energy absorption characteristics of the structures under quasi-static axial compression were evaluated and compared. It was found that all studied thin-walled structures exhibited progressive folding deformation patterns during compression. In particular, energy absorption process was achieved through the combined damage modes of plastic deformation, fiber pullout and delamination. Furthermore, the comparison results showed that the hexagonal structure exhibited the best energy absorption performance. The study revealed the structure-mechanical property relationship of 3D printed continuous fiber reinforced composite thin-walled structures through the analysis of multiscale failure characteristics and load response, which is valuable for broadening their applications.
2023, 36.
doi: 10.1186/s10033-023-00945-y
Abstract:
Fast and accurate measurement of the volume of earthmoving materials is of great significance for the real-time evaluation of loader operation efficiency and the realization of autonomous operation. Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader’s shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fill factor estimation, and it has significant theoretical research and engineering application value.
Fast and accurate measurement of the volume of earthmoving materials is of great significance for the real-time evaluation of loader operation efficiency and the realization of autonomous operation. Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader’s shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fill factor estimation, and it has significant theoretical research and engineering application value.
2023, 36.
doi: 10.1186/s10033-023-00948-9
Abstract:
Owing to the popularization of coating technology, physical Vapor Deposition (PVD) coated tools have become indispensable in the cutting process. Additionally, the post-treatment of coated tools applied to industrial production can effectively enhance the surface quality of coating. To improve the processing performance of coated tools, micro abrasive slurry jet (MASJ) polishing technology is first applied to the post-treatment of coated tools. Subsequently, the effects of process parameters on the surface quality and cutting thickness of coating are investigated via single-factor experiments. In the experiment, the best surface roughness is obtained by setting the working pressure to 0.4 MPa, particle size to 3 μm, incidence angle to 30°, and abrasive mass concentration to 100 g/L. Based on the results of the single-factor experiments, combination experiments are designed, and three types of coated tools with different surface qualities and coating thicknesses are obtained. The MASJ process for the post-treatment of coated tools is investigated based on a tool wear experiment and the effects of cutting parameters on the cutting force and workpiece surface quality of three types of cutting tools. The result indicates that MASJ machining can effectively improve the machining performance of coated tools.
Owing to the popularization of coating technology, physical Vapor Deposition (PVD) coated tools have become indispensable in the cutting process. Additionally, the post-treatment of coated tools applied to industrial production can effectively enhance the surface quality of coating. To improve the processing performance of coated tools, micro abrasive slurry jet (MASJ) polishing technology is first applied to the post-treatment of coated tools. Subsequently, the effects of process parameters on the surface quality and cutting thickness of coating are investigated via single-factor experiments. In the experiment, the best surface roughness is obtained by setting the working pressure to 0.4 MPa, particle size to 3 μm, incidence angle to 30°, and abrasive mass concentration to 100 g/L. Based on the results of the single-factor experiments, combination experiments are designed, and three types of coated tools with different surface qualities and coating thicknesses are obtained. The MASJ process for the post-treatment of coated tools is investigated based on a tool wear experiment and the effects of cutting parameters on the cutting force and workpiece surface quality of three types of cutting tools. The result indicates that MASJ machining can effectively improve the machining performance of coated tools.
2023, 36.
doi: 10.1186/s10033-023-00960-z
Abstract:
Ultrasonic testing (UT) is increasingly combined with machine learning (ML) techniques for intelligently identifying damage. Extracting significant features from UT data is essential for efficient defect characterization. Moreover, the hidden physics behind ML is unexplained, reducing the generalization capability and versatility of ML methods in UT. In this paper, a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efficiency of UT. Firstly, multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space. Subsequently, a feature selection method based on model interpretable strategy (FS-MIS) is innovatively developed by integrating Shapley additive explanation (SHAP), filter method, embedded method and wrapper method. The most effective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively. The proposed framework is validated by identifying and locating side-drilled holes (SDHs) with 0.5λ central distance and different depths. An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments. The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival (ToAs) of the scattered waves emitted by adjacent SDHs. The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67% with an average error of 0.25%, significantly improving the time resolution of UT signals. On this basis, the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets. The imaging resolution is enhanced to 0.5λ by implementing the total focusing method (TFM). The relative errors of hole depths and central distance are no more than 0.51% and 3.57%, respectively. Finally, the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.
Ultrasonic testing (UT) is increasingly combined with machine learning (ML) techniques for intelligently identifying damage. Extracting significant features from UT data is essential for efficient defect characterization. Moreover, the hidden physics behind ML is unexplained, reducing the generalization capability and versatility of ML methods in UT. In this paper, a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efficiency of UT. Firstly, multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space. Subsequently, a feature selection method based on model interpretable strategy (FS-MIS) is innovatively developed by integrating Shapley additive explanation (SHAP), filter method, embedded method and wrapper method. The most effective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively. The proposed framework is validated by identifying and locating side-drilled holes (SDHs) with 0.5λ central distance and different depths. An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments. The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival (ToAs) of the scattered waves emitted by adjacent SDHs. The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67% with an average error of 0.25%, significantly improving the time resolution of UT signals. On this basis, the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets. The imaging resolution is enhanced to 0.5λ by implementing the total focusing method (TFM). The relative errors of hole depths and central distance are no more than 0.51% and 3.57%, respectively. Finally, the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.
2023, 36.
doi: 10.1186/s10033-023-00970-x
Abstract:
Mining shovel is a crucial piece of equipment for high-efficiency production in open-pit mining and stands as one of the largest energy consumption sources in mining. However, substantial energy waste occurs during the descent of the hoisting system or the deceleration of the slewing platform. To reduce the energy loss, an innovative hydraulic-electric hybrid drive system is proposed, in which a hydraulic pump/motor connected with an accumulator is added to assist the electric motor to drive the hoisting system or slewing platform, recycling kinetic and potential energy. The utilization of the kinetic and potential energy reduces the energy loss and installed power of the mining shovel. Meanwhile, the reliability of the mining shovel pure electric drive system also can be increased. In this paper, the hydraulic-electric hybrid driving principle is introduced, a small-scale testbed is set up to verify the feasibility of the system, and a co-simulation model of the proposed system is established to clarify the system operation and energy characteristics. The test and simulation results show that, by adopting the proposed system, compared with the traditional purely electric driving system, the peak power and energy consumption of the hoisting electric motor are reduced by 36.7% and 29.7%, respectively. Similarly, the slewing electric motor experiences a significant decrease in peak power by 86.9% and a reduction in energy consumption by 59.4%. The proposed system expands the application area of the hydraulic electric hybrid drive system and provides a reference for its application in oversized and super heavy equipment.
Mining shovel is a crucial piece of equipment for high-efficiency production in open-pit mining and stands as one of the largest energy consumption sources in mining. However, substantial energy waste occurs during the descent of the hoisting system or the deceleration of the slewing platform. To reduce the energy loss, an innovative hydraulic-electric hybrid drive system is proposed, in which a hydraulic pump/motor connected with an accumulator is added to assist the electric motor to drive the hoisting system or slewing platform, recycling kinetic and potential energy. The utilization of the kinetic and potential energy reduces the energy loss and installed power of the mining shovel. Meanwhile, the reliability of the mining shovel pure electric drive system also can be increased. In this paper, the hydraulic-electric hybrid driving principle is introduced, a small-scale testbed is set up to verify the feasibility of the system, and a co-simulation model of the proposed system is established to clarify the system operation and energy characteristics. The test and simulation results show that, by adopting the proposed system, compared with the traditional purely electric driving system, the peak power and energy consumption of the hoisting electric motor are reduced by 36.7% and 29.7%, respectively. Similarly, the slewing electric motor experiences a significant decrease in peak power by 86.9% and a reduction in energy consumption by 59.4%. The proposed system expands the application area of the hydraulic electric hybrid drive system and provides a reference for its application in oversized and super heavy equipment.
2023, 36.
doi: 10.1186/s10033-023-00938-x
Abstract:
Polyoxymethylene methacrylate (PMMA) is widely used in ophthalmic biomaterials. Misuse of PMMA in extreme environments is likely to damage the ocular surface and intraocular structures. The surface characterization and tribological behavior of PMMA processed using an excimer laser were investigated in this study by contrasting different lubrication conditions and friction cycles. The results show that the roughness of the material surface increases with laser processing, which changes its physical structure. Under lubrication, the laser-treated PMMA exhibits better hydrophilicity, especially during the use of eye drops. No obvious relationship exists between the laser-processing time and friction behavior. However, the laser treatment may contribute to the formation of friction and wear mechanisms of PMMA materials. Laser-treated PMMA in saline solution exhibits better abrasive resistance by showing a lower wear rate than that in eye drops, although it has a higher friction coefficient. In this study, the different friction stages in laser-treated PMMA were clarified under two lubrication conditions. The wear rates of the laser-treated PMMA were found to decrease with the number of cycles, and the friction coefficient has a similar variation tendency. The wear behavior of the laser-treated PMMA is dominated by the main abrasive wear and secondary transferred film formation. This study provides a theoretical basis for the development and application of ophthalmic biomaterials in complex environments by examining the material surface interface behavior and wear mechanism after laser processing using PMMA as the research matrix.
Polyoxymethylene methacrylate (PMMA) is widely used in ophthalmic biomaterials. Misuse of PMMA in extreme environments is likely to damage the ocular surface and intraocular structures. The surface characterization and tribological behavior of PMMA processed using an excimer laser were investigated in this study by contrasting different lubrication conditions and friction cycles. The results show that the roughness of the material surface increases with laser processing, which changes its physical structure. Under lubrication, the laser-treated PMMA exhibits better hydrophilicity, especially during the use of eye drops. No obvious relationship exists between the laser-processing time and friction behavior. However, the laser treatment may contribute to the formation of friction and wear mechanisms of PMMA materials. Laser-treated PMMA in saline solution exhibits better abrasive resistance by showing a lower wear rate than that in eye drops, although it has a higher friction coefficient. In this study, the different friction stages in laser-treated PMMA were clarified under two lubrication conditions. The wear rates of the laser-treated PMMA were found to decrease with the number of cycles, and the friction coefficient has a similar variation tendency. The wear behavior of the laser-treated PMMA is dominated by the main abrasive wear and secondary transferred film formation. This study provides a theoretical basis for the development and application of ophthalmic biomaterials in complex environments by examining the material surface interface behavior and wear mechanism after laser processing using PMMA as the research matrix.
2023, 36.
doi: 10.1186/s10033-023-00971-w
Abstract:
Magnetically coupled rodless cylinders are widely used in the coordinate positioning of mechanical arms, electrostatic paintings, and other industrial applications. However, they exhibit strong nonlinear characteristics, which lead to low servo control accuracy. In this study, a mass-flow equation through the valve port was derived to improve the control performance, considering the characteristics of the dynamics and throttle-hole flow. Subsequently, a friction model combining static, viscous, and Coulomb friction with a zero-velocity interval was proposed. In addition, energy and dynamic models were set for the experimental investigation of the magnetically coupled rodless cylinder. A nonlinear mathematical model for the position of the magnetically coupled rodless cylinder was proposed. An incremental PID controller was designed for the magnetically coupled rodless cylinder to control this system, and the PID parameters were adjusted online using RBF neural network. The response results of the PID parameters based on the RBF neural network were compared with those of the traditional incremental PID control, which proved the superiority of the optimization control algorithm of the incremental PID parameters based on the RBF neural network servo control system. The experimental results of this model were compared with the simulation results. The average error between the established model and the actual system was 0.005175054 (m), which was approximately 2.588% of the total travel length, demonstrating the accuracy of the theoretical model.
Magnetically coupled rodless cylinders are widely used in the coordinate positioning of mechanical arms, electrostatic paintings, and other industrial applications. However, they exhibit strong nonlinear characteristics, which lead to low servo control accuracy. In this study, a mass-flow equation through the valve port was derived to improve the control performance, considering the characteristics of the dynamics and throttle-hole flow. Subsequently, a friction model combining static, viscous, and Coulomb friction with a zero-velocity interval was proposed. In addition, energy and dynamic models were set for the experimental investigation of the magnetically coupled rodless cylinder. A nonlinear mathematical model for the position of the magnetically coupled rodless cylinder was proposed. An incremental PID controller was designed for the magnetically coupled rodless cylinder to control this system, and the PID parameters were adjusted online using RBF neural network. The response results of the PID parameters based on the RBF neural network were compared with those of the traditional incremental PID control, which proved the superiority of the optimization control algorithm of the incremental PID parameters based on the RBF neural network servo control system. The experimental results of this model were compared with the simulation results. The average error between the established model and the actual system was 0.005175054 (m), which was approximately 2.588% of the total travel length, demonstrating the accuracy of the theoretical model.
2023, 36.
doi: 10.1186/s10033-023-00951-0
Abstract:
With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efficient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difficult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identification is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identification models. The experimental results proved the superiority of the HDT framework for human locomotion mode identification.
With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efficient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difficult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identification is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identification models. The experimental results proved the superiority of the HDT framework for human locomotion mode identification.
2023, 36.
doi: 10.1186/s10033-023-00946-x
Abstract:
Nonlinear friction is a dominant factor affecting the control accuracy of CNC machine tools. This paper proposes a friction pre-compensation method for CNC machine tools through constructing a nonlinear model predictive scheme. The nonlinear friction-induced tracking error is firstly modeled and then utilized to establish the nonlinear model predictive scheme, which is subsequently used to optimize the compensation signal by treating the friction-induced tracking error as the optimization objective. During the optimization procedure, the derivative of compensation signal is constrained to avoid vibration of machine tools. In contrast to other existing approaches, the proposed method only needs the parameters of Stribeck friction model and an additional tuning parameter, while finely identifying the parameters related to the pre-sliding phenomenon is not required. As a result, it greatly facilitates the practical applicability. Both air cutting and real cutting experiments conducted on an in-house developed open-architecture CNC machine tool prove that the proposed method can reduce the tracking errors by more than 56%, and reduce the contour errors by more than 50%.
Nonlinear friction is a dominant factor affecting the control accuracy of CNC machine tools. This paper proposes a friction pre-compensation method for CNC machine tools through constructing a nonlinear model predictive scheme. The nonlinear friction-induced tracking error is firstly modeled and then utilized to establish the nonlinear model predictive scheme, which is subsequently used to optimize the compensation signal by treating the friction-induced tracking error as the optimization objective. During the optimization procedure, the derivative of compensation signal is constrained to avoid vibration of machine tools. In contrast to other existing approaches, the proposed method only needs the parameters of Stribeck friction model and an additional tuning parameter, while finely identifying the parameters related to the pre-sliding phenomenon is not required. As a result, it greatly facilitates the practical applicability. Both air cutting and real cutting experiments conducted on an in-house developed open-architecture CNC machine tool prove that the proposed method can reduce the tracking errors by more than 56%, and reduce the contour errors by more than 50%.
2023, 36.
doi: 10.1186/s10033-023-00969-4
Abstract:
The significance of liquids in abrasive wire sawing has been demonstrated in several studies. However, the performance of its spreading behavior is limited by the current development trend, where the wafer has a larger area and the kerf is narrower. Moreover, there are very few studies on the liquid spreading behavior in wire-sawn kerfs. Therefore, a 3D CFD (computational fluid dynamics) model is presented in this paper and used to simulate the liquid spreading behavior in a kerf based on a VOF (volume of fluid) method with a CSF (continuum surface force) model, which is used to simulate multiphase flow, and an empirical correlation for characterizing the liquid dynamic contact angle using UDF (user defined functions). Subsequently, parametric simulations are performed on the kerf area, kerf width, liquid viscosity, liquid surface tension, and liquid velocity at the inlet area of the kerf, and verification experiments are conducted to determine the validity of the simulation model. From the simulation and experimental results, three typical liquid spreading regimes that exhibit different effects on wire sawing in the kerfs are found, and their limiting conditions are identified using non-dimensional analysis. Subsequently, a prediction model is proposed for the liquid spreading regime based on a set of Weber and Capillary numbers. For wire sawing, an increase in the wafer area does not change the liquid spreading regime in the kerf; however, a reduction in the kerf width significantly hinders the liquid spreading behavior. Thereby, the spreading regime can be effectively converted to facilitate wire sawing by adjusting the physical properties and supply conditions of the liquid.
The significance of liquids in abrasive wire sawing has been demonstrated in several studies. However, the performance of its spreading behavior is limited by the current development trend, where the wafer has a larger area and the kerf is narrower. Moreover, there are very few studies on the liquid spreading behavior in wire-sawn kerfs. Therefore, a 3D CFD (computational fluid dynamics) model is presented in this paper and used to simulate the liquid spreading behavior in a kerf based on a VOF (volume of fluid) method with a CSF (continuum surface force) model, which is used to simulate multiphase flow, and an empirical correlation for characterizing the liquid dynamic contact angle using UDF (user defined functions). Subsequently, parametric simulations are performed on the kerf area, kerf width, liquid viscosity, liquid surface tension, and liquid velocity at the inlet area of the kerf, and verification experiments are conducted to determine the validity of the simulation model. From the simulation and experimental results, three typical liquid spreading regimes that exhibit different effects on wire sawing in the kerfs are found, and their limiting conditions are identified using non-dimensional analysis. Subsequently, a prediction model is proposed for the liquid spreading regime based on a set of Weber and Capillary numbers. For wire sawing, an increase in the wafer area does not change the liquid spreading regime in the kerf; however, a reduction in the kerf width significantly hinders the liquid spreading behavior. Thereby, the spreading regime can be effectively converted to facilitate wire sawing by adjusting the physical properties and supply conditions of the liquid.
2023, 36.
doi: 10.1186/s10033-023-00949-8
Abstract:
The existence of the relative radial and axial movements of a revolute joint's journal and bearing is widely known. The three-dimensional (3D) revolute joint model considers relative radial and axial clearances; therefore, the freedoms of motion and contact scenarios are more realistic than those of the two-dimensional model. This paper proposes a wear model that integrates the modeling of a 3D revolute clearance joint and the contact force and wear depth calculations. Time-varying contact stiffness is first considered in the contact force model. Also, a cycle-update wear depth calculation strategy is presented. A digital image correlation (DIC) non-contact measurement and a cylindricity test are conducted. The measurement results are compared with the numerical simulation, and the proposed model's correctness and the wear depth calculation strategy are verified. The results show that the wear amount distribution on the bearing's inner surface is uneven in the axial and radial directions due to the journal's stochastic oscillations. The maximum wear depth locates where at the bearing's edges the motion direction of the follower shifts. These findings help to seek the revolute joints' wear-prone parts and enhance their durability and reliability through improved design.
The existence of the relative radial and axial movements of a revolute joint's journal and bearing is widely known. The three-dimensional (3D) revolute joint model considers relative radial and axial clearances; therefore, the freedoms of motion and contact scenarios are more realistic than those of the two-dimensional model. This paper proposes a wear model that integrates the modeling of a 3D revolute clearance joint and the contact force and wear depth calculations. Time-varying contact stiffness is first considered in the contact force model. Also, a cycle-update wear depth calculation strategy is presented. A digital image correlation (DIC) non-contact measurement and a cylindricity test are conducted. The measurement results are compared with the numerical simulation, and the proposed model's correctness and the wear depth calculation strategy are verified. The results show that the wear amount distribution on the bearing's inner surface is uneven in the axial and radial directions due to the journal's stochastic oscillations. The maximum wear depth locates where at the bearing's edges the motion direction of the follower shifts. These findings help to seek the revolute joints' wear-prone parts and enhance their durability and reliability through improved design.
2023, 36.
doi: 10.1186/s10033-023-00957-8
Abstract:
Micro-grinding with a spherical grinding head has been deemed an indispensable method in high-risk surgeries, such as neurosurgery and spine surgery, where bone grinding has long been plagued by the technical bottleneck of mechanical stress-induced crack damage. In response to this challenge, the ultrasound-assisted biological bone micro-grinding novel process with a spherical grinding head has been proposed by researchers. Force modeling is a prerequisite for process parameter determination in orthopedic surgery, and the difficulty in establishing and accurately predicting bone micro-grinding force prediction models is due to the geometric distribution of abrasive grains and the dynamic changes in geometry and kinematics during the cutting process. In addressing these critical needs and technical problems, the shape and protrusion heights of the wear particle of the spherical grinding head were first studied, and the gradual rule of the contact arc length under the action of high-speed rotating ultrasonic vibration was proposed. Second, the mathematical model of the maximum thickness of undeformed chips under ultrasonic vibration of the spherical grinding head was established. Results showed that ultrasonic vibration can reduce the maximum thickness of undeformed chips and increase the range of ductile and bone meal removals, revealing the mechanism of reducing grinding force. Further, the dynamic grinding behavior of different layers of abrasive particles under different instantaneous interaction states was studied. Finally, a prediction model of micro-grinding force was established in accordance with the relationship between grinding force and cutting depth, revealing the mechanism of micro-grinding force transfer under ultrasonic vibration. The theoretical model's average deviations are 10.37% in x-axis direction, 6.85% in y-axis direction, and 7.81% in z-axis direction compared with the experimental results. This study provides theoretical guidance and technical support for clinical bone micro-grinding.
Micro-grinding with a spherical grinding head has been deemed an indispensable method in high-risk surgeries, such as neurosurgery and spine surgery, where bone grinding has long been plagued by the technical bottleneck of mechanical stress-induced crack damage. In response to this challenge, the ultrasound-assisted biological bone micro-grinding novel process with a spherical grinding head has been proposed by researchers. Force modeling is a prerequisite for process parameter determination in orthopedic surgery, and the difficulty in establishing and accurately predicting bone micro-grinding force prediction models is due to the geometric distribution of abrasive grains and the dynamic changes in geometry and kinematics during the cutting process. In addressing these critical needs and technical problems, the shape and protrusion heights of the wear particle of the spherical grinding head were first studied, and the gradual rule of the contact arc length under the action of high-speed rotating ultrasonic vibration was proposed. Second, the mathematical model of the maximum thickness of undeformed chips under ultrasonic vibration of the spherical grinding head was established. Results showed that ultrasonic vibration can reduce the maximum thickness of undeformed chips and increase the range of ductile and bone meal removals, revealing the mechanism of reducing grinding force. Further, the dynamic grinding behavior of different layers of abrasive particles under different instantaneous interaction states was studied. Finally, a prediction model of micro-grinding force was established in accordance with the relationship between grinding force and cutting depth, revealing the mechanism of micro-grinding force transfer under ultrasonic vibration. The theoretical model's average deviations are 10.37% in x-axis direction, 6.85% in y-axis direction, and 7.81% in z-axis direction compared with the experimental results. This study provides theoretical guidance and technical support for clinical bone micro-grinding.
2023, 36.
doi: 10.1186/s10033-023-00939-w
Abstract:
The low density and high corrosion resistance of titanium alloy make it a material with various applications in the aerospace industry. However, because of its high specific strength and poor thermal conductivity, there are problems such as high cutting force, poor surface integrity, and high cutting temperature during conventional machining. As an advanced processing method with high efficiency and low damage, laser-assisted machining can improve the machinability of titanium alloy. In this study, a picosecond pulse laser-assisted scratching (PPLAS) method considering both the temperature-dependent material properties and ultrashort pulse laser’s characteristics is first proposed. Then, the effects of laser power, scratching depth, and scratching speed on the distribution of stress and temperature field are investigated by simulation. Next, PPLAS experiments are conducted to verify the correctness of the simulation and reveal the removal behavior at various combinations of laser power and scratching depths. Finally, combined with simulated and experimental results, the removal mechanism under the two machining methods is illustrated. Compared with conventional scratching (CS), the tangential grinding force is reduced by more than 60% and the material removal degree is up to 0.948 during PPLAS, while the material removal is still primarily in the form of plastic removal. Grinding debris in CS takes the form of stacked flakes with a “fish scale” surface, whereas it takes the form of broken serrations in PPLAS. This research can provide important guidance for titanium alloy grinding with high surface quality and low surface damage.
The low density and high corrosion resistance of titanium alloy make it a material with various applications in the aerospace industry. However, because of its high specific strength and poor thermal conductivity, there are problems such as high cutting force, poor surface integrity, and high cutting temperature during conventional machining. As an advanced processing method with high efficiency and low damage, laser-assisted machining can improve the machinability of titanium alloy. In this study, a picosecond pulse laser-assisted scratching (PPLAS) method considering both the temperature-dependent material properties and ultrashort pulse laser’s characteristics is first proposed. Then, the effects of laser power, scratching depth, and scratching speed on the distribution of stress and temperature field are investigated by simulation. Next, PPLAS experiments are conducted to verify the correctness of the simulation and reveal the removal behavior at various combinations of laser power and scratching depths. Finally, combined with simulated and experimental results, the removal mechanism under the two machining methods is illustrated. Compared with conventional scratching (CS), the tangential grinding force is reduced by more than 60% and the material removal degree is up to 0.948 during PPLAS, while the material removal is still primarily in the form of plastic removal. Grinding debris in CS takes the form of stacked flakes with a “fish scale” surface, whereas it takes the form of broken serrations in PPLAS. This research can provide important guidance for titanium alloy grinding with high surface quality and low surface damage.
2023, 36.
doi: 10.1186/s10033-023-00913-6
Abstract:
To address the problem of conventional approaches for mechanical property determination requiring destructive sampling, which may be unsuitable for in-service structures, the authors proposed a method for determining the quasi-static fracture toughness and impact absorbed energy of ductile metals from spherical indentation tests (SITs). The stress status and damage mechanism of SIT, mode I fracture, Charpy impact tests, and related tests were first investigated through finite element (FE) calculations and scanning electron microscopy (SEM) observations, respectively. It was found that the damage mechanism of SITs is different from that of mode I fractures, while mode I fractures and Charpy impact tests share the same damage mechanism. Considering the difference between SIT and mode I fractures, uniaxial tension and pure shear were introduced to correlate SIT with mode I fractures. Based on this, the widely used critical indentation energy (CIE) model for fracture toughness determination using SITs was modified. The quasi-static fracture toughness determined from the modified CIE model was used to evaluate the impact absorbed energy using the dynamic fracture toughness and energy for crack initiation. The effectiveness of the newly proposed method was verified through experiments on four types of steels: Q345R, SA508-3, 18MnMoNbR, and S30408.
To address the problem of conventional approaches for mechanical property determination requiring destructive sampling, which may be unsuitable for in-service structures, the authors proposed a method for determining the quasi-static fracture toughness and impact absorbed energy of ductile metals from spherical indentation tests (SITs). The stress status and damage mechanism of SIT, mode I fracture, Charpy impact tests, and related tests were first investigated through finite element (FE) calculations and scanning electron microscopy (SEM) observations, respectively. It was found that the damage mechanism of SITs is different from that of mode I fractures, while mode I fractures and Charpy impact tests share the same damage mechanism. Considering the difference between SIT and mode I fractures, uniaxial tension and pure shear were introduced to correlate SIT with mode I fractures. Based on this, the widely used critical indentation energy (CIE) model for fracture toughness determination using SITs was modified. The quasi-static fracture toughness determined from the modified CIE model was used to evaluate the impact absorbed energy using the dynamic fracture toughness and energy for crack initiation. The effectiveness of the newly proposed method was verified through experiments on four types of steels: Q345R, SA508-3, 18MnMoNbR, and S30408.
2023, 36.
doi: 10.1186/s10033-023-00941-2
Abstract:
Improved energy utilisation, precision, and quality are critical in the current trend of low-carbon green manufacturing. In this study, three abrasive belts were prepared at various wear stages and characterised quantitatively. The effects of abrasive belt wear on the specific grinding energy partition were investigated by evaluating robotic belt grinding of titanium plates. A specific grinding energy model based on subdivided tangential forces of cutting and sliding was developed for investigating specific energy and energy utilisation coefficient EUC. The surface morphology and Abbott–Firestone curves of the belts were introduced to analyse the experimental findings from the perspective of the micro cutting behaviour. The specific grinding energy increased with abrasive belt wear, especially when the belt was near the end of its life. Moreover, the belt wear could lead to a predominance change of sliding and chip formation energy. The highest EUC was observed in the middle of the belt life because of its retained sharp cutting edge and uniform distribution of the grit protrusion height. This study provides guidance for balancing the energy consumption and energy utilization efficiency of belt grinding.
Improved energy utilisation, precision, and quality are critical in the current trend of low-carbon green manufacturing. In this study, three abrasive belts were prepared at various wear stages and characterised quantitatively. The effects of abrasive belt wear on the specific grinding energy partition were investigated by evaluating robotic belt grinding of titanium plates. A specific grinding energy model based on subdivided tangential forces of cutting and sliding was developed for investigating specific energy and energy utilisation coefficient EUC. The surface morphology and Abbott–Firestone curves of the belts were introduced to analyse the experimental findings from the perspective of the micro cutting behaviour. The specific grinding energy increased with abrasive belt wear, especially when the belt was near the end of its life. Moreover, the belt wear could lead to a predominance change of sliding and chip formation energy. The highest EUC was observed in the middle of the belt life because of its retained sharp cutting edge and uniform distribution of the grit protrusion height. This study provides guidance for balancing the energy consumption and energy utilization efficiency of belt grinding.
2023, 36: 2.
doi: 10.1186/s10033-022-00828-8
Abstract:
Burnishing experiments with different burnishing parameters were performed on a computer numerical control milling machine to characterize the surface roughness of an aluminum alloy during burnishing. The chaos theory was employed to investigate the nonlinear features of the burnishing system. The experimental results show that the power spectrum is broadband and continuous, and the Lyapunov exponent λ is positive, proving that burnishing has chaotic characteristics. The chaotic characteristic parameter, the correlation dimension D, is sensitive to the time behavior of the system and is used to establish the corresponding relationship with the surface roughness. The correlation dimension was the largest, when the surface roughness was the smallest. Furthermore, when the correlation dimension curve decreases, the roughness curve increases. The correlation dimension and surface roughness exhibit opposite variation trends. The higher the correlation dimension, the lower the surface roughness. The surface roughness of the aluminum alloy can be characterized online by calculating the correlation dimension during burnishing.
Burnishing experiments with different burnishing parameters were performed on a computer numerical control milling machine to characterize the surface roughness of an aluminum alloy during burnishing. The chaos theory was employed to investigate the nonlinear features of the burnishing system. The experimental results show that the power spectrum is broadband and continuous, and the Lyapunov exponent λ is positive, proving that burnishing has chaotic characteristics. The chaotic characteristic parameter, the correlation dimension D, is sensitive to the time behavior of the system and is used to establish the corresponding relationship with the surface roughness. The correlation dimension was the largest, when the surface roughness was the smallest. Furthermore, when the correlation dimension curve decreases, the roughness curve increases. The correlation dimension and surface roughness exhibit opposite variation trends. The higher the correlation dimension, the lower the surface roughness. The surface roughness of the aluminum alloy can be characterized online by calculating the correlation dimension during burnishing.
2023, 36: 4.
doi: 10.1186/s10033-022-00825-x
Abstract:
Contour bevel gears have the advantages of high coincidence, low noise and large bearing capacity, which are widely used in automobile manufacturing, shipbuilding and construction machinery. However, when the surface quality is poor, the effective contact area between the gear mating surfaces decreases, affecting the stability of the fit and thus the transmission accuracy, so it is of great significance to optimize the surface quality of the contour bevel gear. This paper firstly analyzes the formation process of machined surface roughness of contour bevel gears on the basis of generating machining method, and dry milling experiments of contour bevel gears are conducted to analyze the effects of cutting speed and feed rate on the machined surface roughness and surface topography of the workpiece. Then, the surface defects on the machined surface of the workpiece are studied by SEM, and the causes of the surface defects are analyzed by EDS. After that, XRD is used to compare the microscopic grains of the machined surface and the substrate material for diffraction peak analysis, and the effect of cutting parameters on the microhardness of the workpiece machined surface is investigated by work hardening experiment. The research results are of great significance for improving the machining accuracy of contour bevel gears, reducing friction losses and improving transmission efficiency.
Contour bevel gears have the advantages of high coincidence, low noise and large bearing capacity, which are widely used in automobile manufacturing, shipbuilding and construction machinery. However, when the surface quality is poor, the effective contact area between the gear mating surfaces decreases, affecting the stability of the fit and thus the transmission accuracy, so it is of great significance to optimize the surface quality of the contour bevel gear. This paper firstly analyzes the formation process of machined surface roughness of contour bevel gears on the basis of generating machining method, and dry milling experiments of contour bevel gears are conducted to analyze the effects of cutting speed and feed rate on the machined surface roughness and surface topography of the workpiece. Then, the surface defects on the machined surface of the workpiece are studied by SEM, and the causes of the surface defects are analyzed by EDS. After that, XRD is used to compare the microscopic grains of the machined surface and the substrate material for diffraction peak analysis, and the effect of cutting parameters on the microhardness of the workpiece machined surface is investigated by work hardening experiment. The research results are of great significance for improving the machining accuracy of contour bevel gears, reducing friction losses and improving transmission efficiency.
2023, 36: 5.
doi: 10.1186/s10033-022-00827-9
Abstract:
This study is concerned with the surface integrity of Inconel 738LC parts manufactured by selective laser melting (SLM) followed by high-speed milling (HSM). In the investigation process of surface integrity, the study employs ultradepth three-dimensional microscopy, laser scanning confocal microscopy, scanning electron microscopy, electron backscatter diffractometry, and energy dispersive spectroscopy to characterize the evolution of material microstructure, work hardening, residual stress coupling, and anisotropic effect of the building direction on surface integrity of the samples. The results show that SLM/HSM hybrid manufacturing can be an effective method to obtain better surface quality with a thinner machining metamorphic layer. High-speed machining is adopted to reduce cutting force and suppress machining heat, which is an effective way to produce better surface mechanical properties during the SLM/HSM hybrid manufacturing process. In general, high-speed milling of the SLM-built Inconel 738LC samples offers better surface integrity, compared to simplex additive manufacturing or casting.
This study is concerned with the surface integrity of Inconel 738LC parts manufactured by selective laser melting (SLM) followed by high-speed milling (HSM). In the investigation process of surface integrity, the study employs ultradepth three-dimensional microscopy, laser scanning confocal microscopy, scanning electron microscopy, electron backscatter diffractometry, and energy dispersive spectroscopy to characterize the evolution of material microstructure, work hardening, residual stress coupling, and anisotropic effect of the building direction on surface integrity of the samples. The results show that SLM/HSM hybrid manufacturing can be an effective method to obtain better surface quality with a thinner machining metamorphic layer. High-speed machining is adopted to reduce cutting force and suppress machining heat, which is an effective way to produce better surface mechanical properties during the SLM/HSM hybrid manufacturing process. In general, high-speed milling of the SLM-built Inconel 738LC samples offers better surface integrity, compared to simplex additive manufacturing or casting.
2023, 36: 6.
doi: 10.1186/s10033-022-00829-7
Abstract:
The use of terahertz time-domain spectroscopy (THz-TDS) for the nondestructive testing and evaluation (NDT & E) of materials and structural systems has attracted significant attention over the past two decades due to its superior spatial resolution and capabilities of detecting and characterizing defects and structural damage in non-conducting materials. In this study, the THz-TDS system is used to detect, localize and evaluate hidden multi-delamination defects (i.e., a three-level multi-delamination system) in multilayered GFRP composite laminates. To obtain accurate results, a wavelet shrinkage de-noising algorithm is used to remove the noise from the measured time-of-flight (TOF) signals. The thickness and location of each delamination defect in the z-direction (i.e., through-the-thickness direction) are calculated from the de-noised TOF signals considering the interaction between the pulsed THz waves and the different interfaces in the GFRP composite laminates. A comparison between the actual and the measured thickness values of the delamination defects before and after the wavelet shrinkage denoising process indicates that the latter provides better results with less than 3.712% relative error, while the relative error of the non-de-noised signals reaches 16.388%. Also, the power and absorbance levels of the THz waves at every interface with different refractive indices in the GFRP composite laminates are evaluated based on analytical and experimental approaches. The present study provides an adequate theoretical analysis that could help NDT & E specialists to estimate the maximum thickness of GFRP composite materials and/or structures with different interfaces that can be evaluated by the THz-TDS. Also, the accuracy of the obtained results highlights the capabilities of the THz-TDS for the NDT & E of multilayered GFRP composite laminates.
The use of terahertz time-domain spectroscopy (THz-TDS) for the nondestructive testing and evaluation (NDT & E) of materials and structural systems has attracted significant attention over the past two decades due to its superior spatial resolution and capabilities of detecting and characterizing defects and structural damage in non-conducting materials. In this study, the THz-TDS system is used to detect, localize and evaluate hidden multi-delamination defects (i.e., a three-level multi-delamination system) in multilayered GFRP composite laminates. To obtain accurate results, a wavelet shrinkage de-noising algorithm is used to remove the noise from the measured time-of-flight (TOF) signals. The thickness and location of each delamination defect in the z-direction (i.e., through-the-thickness direction) are calculated from the de-noised TOF signals considering the interaction between the pulsed THz waves and the different interfaces in the GFRP composite laminates. A comparison between the actual and the measured thickness values of the delamination defects before and after the wavelet shrinkage denoising process indicates that the latter provides better results with less than 3.712% relative error, while the relative error of the non-de-noised signals reaches 16.388%. Also, the power and absorbance levels of the THz waves at every interface with different refractive indices in the GFRP composite laminates are evaluated based on analytical and experimental approaches. The present study provides an adequate theoretical analysis that could help NDT & E specialists to estimate the maximum thickness of GFRP composite materials and/or structures with different interfaces that can be evaluated by the THz-TDS. Also, the accuracy of the obtained results highlights the capabilities of the THz-TDS for the NDT & E of multilayered GFRP composite laminates.
2023, 36: 9.
doi: 10.1186/s10033-023-00838-0
Abstract:
Deep learning (DL) is progressively popular as a viable alternative to traditional signal processing (SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods difficult to be trusted and understood by industrial users. In addition, the extraction of weak fault features from signals with heavy noise is imperative in industrial applications. To address these limitations, inspired by the Filterbank-Feature-Decision methodology, we propose a new Signal Processing Informed Neural Network (SPINN) framework by embedding SP knowledge into the DL model. As one of the practical implementations for SPINN, a denoising fault-aware wavelet network (DFAWNet) is developed, which consists of fused wavelet convolution (FWConv), dynamic hard thresholding (DHT), index-based soft filtering (ISF), and a classifier. Taking advantage of wavelet transform, FWConv extracts multiscale features while learning wavelet scales and selecting important wavelet bases automatically; DHT dynamically eliminates noise-related components via point-wise hard thresholding; inspired by index-based filtering, ISF optimizes and selects optimal filters for diagnostic feature extraction. It's worth noting that SPINN may be readily applied to different deep learning networks by simply adding filterbank and feature modules in front. Experiments results demonstrate a significant diagnostic performance improvement over other explainable or denoising deep learning networks. The corresponding code is available athttps://github.com/albertszg/DFAWnet .
Deep learning (DL) is progressively popular as a viable alternative to traditional signal processing (SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods difficult to be trusted and understood by industrial users. In addition, the extraction of weak fault features from signals with heavy noise is imperative in industrial applications. To address these limitations, inspired by the Filterbank-Feature-Decision methodology, we propose a new Signal Processing Informed Neural Network (SPINN) framework by embedding SP knowledge into the DL model. As one of the practical implementations for SPINN, a denoising fault-aware wavelet network (DFAWNet) is developed, which consists of fused wavelet convolution (FWConv), dynamic hard thresholding (DHT), index-based soft filtering (ISF), and a classifier. Taking advantage of wavelet transform, FWConv extracts multiscale features while learning wavelet scales and selecting important wavelet bases automatically; DHT dynamically eliminates noise-related components via point-wise hard thresholding; inspired by index-based filtering, ISF optimizes and selects optimal filters for diagnostic feature extraction. It's worth noting that SPINN may be readily applied to different deep learning networks by simply adding filterbank and feature modules in front. Experiments results demonstrate a significant diagnostic performance improvement over other explainable or denoising deep learning networks. The corresponding code is available at
2023, 36: 10.
doi: 10.1186/s10033-023-00839-z
Abstract:
Out-of-plane mechanical properties of the riveted joints restrict the performance of the wing box assembly of airplane. It is necessary to investigate the pull-through performance of the composite/metal riveted joints in order to guide the riveting design and ensure the safety of the wing box assembly. The progressive failure mechanism of composite/aluminum riveted joint subjected to pull-through loading was investigated by experiments and finite element method. A progressive damage model based on the Hashin-type criteria and zero-thickness cohesive zone method was developed by VUMAT subroutine, which was validated by both open-hole tensile test and three-point bending test. Predicted load-displacement response, failure modes and damage propagation were analysed and compared with the results of the pull-through tests. There are 4 obvious characteristic stages on the load-displacement curve of the pull-through test and that of the finite element model: first load take-up stage, damage stage, second load take-up stage and failure stage. Relative error of stiffness, first load peak and second load peak between finite element method and experiments were 8.1%, − 3.3% and 10.6%, respectively. It was found that the specimen was mainly broken by rivet-penetration fracture and delamination of plies of the composite laminate. And the material within the scope of the rivet head is more dangerous with more serious tensile damages than other regions, especially for 90° plies. This study proposes a numerical method for damage prediction and reveals the progressive failure mechanism of the hybrid material riveted joints subjected to the pull-through loading.
Out-of-plane mechanical properties of the riveted joints restrict the performance of the wing box assembly of airplane. It is necessary to investigate the pull-through performance of the composite/metal riveted joints in order to guide the riveting design and ensure the safety of the wing box assembly. The progressive failure mechanism of composite/aluminum riveted joint subjected to pull-through loading was investigated by experiments and finite element method. A progressive damage model based on the Hashin-type criteria and zero-thickness cohesive zone method was developed by VUMAT subroutine, which was validated by both open-hole tensile test and three-point bending test. Predicted load-displacement response, failure modes and damage propagation were analysed and compared with the results of the pull-through tests. There are 4 obvious characteristic stages on the load-displacement curve of the pull-through test and that of the finite element model: first load take-up stage, damage stage, second load take-up stage and failure stage. Relative error of stiffness, first load peak and second load peak between finite element method and experiments were 8.1%, − 3.3% and 10.6%, respectively. It was found that the specimen was mainly broken by rivet-penetration fracture and delamination of plies of the composite laminate. And the material within the scope of the rivet head is more dangerous with more serious tensile damages than other regions, especially for 90° plies. This study proposes a numerical method for damage prediction and reveals the progressive failure mechanism of the hybrid material riveted joints subjected to the pull-through loading.
2023, 36: 12.
doi: 10.1186/s10033-023-00832-6
Abstract:
Harmonic nonlinear ultrasound can offer high sensitivity for residual stress measurements; however, it cannot be used for local stress measurements at a point in space and exhibits nonlinear distortions in the experimental system. This paper presents a feasibility study on the measurement of residual stress in a metal plate using a nonlinear Lamb wave-mixing technique. The resonant conditions for two Lamb waves to generate a mixing frequency wave are obtained via theoretical analysis. Finite element simulations are performed to investigate the nonlinear interactions between the two Lamb waves. Results show that two incident A0 waves interact in regions of material nonlinearity and generate a rightward S0 wave at the sum frequency. Residual stress measurement experiments are conducted on steel plate specimens using the collinear Lamb wave-mixing technique. By setting different delays for two transmitters, the generated sum-frequency component at different spatial locations is measured. Experimental results show that the spatial distribution of the amplitude of the sum-frequency component agrees well with the spatial distribution of the residual stress measured using X-rays. The proposed collinear Lamb wave-mixing method is effective for measuring the distribution of residual stress in metal plates.
Harmonic nonlinear ultrasound can offer high sensitivity for residual stress measurements; however, it cannot be used for local stress measurements at a point in space and exhibits nonlinear distortions in the experimental system. This paper presents a feasibility study on the measurement of residual stress in a metal plate using a nonlinear Lamb wave-mixing technique. The resonant conditions for two Lamb waves to generate a mixing frequency wave are obtained via theoretical analysis. Finite element simulations are performed to investigate the nonlinear interactions between the two Lamb waves. Results show that two incident A0 waves interact in regions of material nonlinearity and generate a rightward S0 wave at the sum frequency. Residual stress measurement experiments are conducted on steel plate specimens using the collinear Lamb wave-mixing technique. By setting different delays for two transmitters, the generated sum-frequency component at different spatial locations is measured. Experimental results show that the spatial distribution of the amplitude of the sum-frequency component agrees well with the spatial distribution of the residual stress measured using X-rays. The proposed collinear Lamb wave-mixing method is effective for measuring the distribution of residual stress in metal plates.
2023, 36: 15.
doi: 10.1186/s10033-022-00824-y
Abstract:
Double-sided lapping is an precision machining method capable of obtaining high-precision surface. However, during the lapping process of thin pure copper substrate, the workpiece will be warped due to the influence of residual stress, including the machining stress and initial residual stress, which will deteriorate the flatness of the workpiece and ultimately affect the performance of components. In this study, finite element method (FEM) was adopted to study the effect of residual stress-related on the deformation of pure copper substrate during double-sided lapping. Considering the initial residual stress of the workpiece, the stress caused by the lapping and their distribution characteristics, a prediction model was proposed for simulating workpiece machining deformation in lapping process by measuring the material removal rate of the upper and lower surfaces of the workpiece under the corresponding parameters. The results showed that the primary cause of the warping deformation of the workpiece in the double-sided lapping is the redistribution of initial residual stress caused by uneven material removal on the both surfaces. The finite element simulation results were in good agreement with the experimental results.
Double-sided lapping is an precision machining method capable of obtaining high-precision surface. However, during the lapping process of thin pure copper substrate, the workpiece will be warped due to the influence of residual stress, including the machining stress and initial residual stress, which will deteriorate the flatness of the workpiece and ultimately affect the performance of components. In this study, finite element method (FEM) was adopted to study the effect of residual stress-related on the deformation of pure copper substrate during double-sided lapping. Considering the initial residual stress of the workpiece, the stress caused by the lapping and their distribution characteristics, a prediction model was proposed for simulating workpiece machining deformation in lapping process by measuring the material removal rate of the upper and lower surfaces of the workpiece under the corresponding parameters. The results showed that the primary cause of the warping deformation of the workpiece in the double-sided lapping is the redistribution of initial residual stress caused by uneven material removal on the both surfaces. The finite element simulation results were in good agreement with the experimental results.
2023, 36: 16.
doi: 10.1186/s10033-023-00852-2
Abstract:
A novel buckling-induced forming method is proposed to produce metal bellows. The tube billet is firstly treated by local heating and cooling, and the axial loading is applied on both ends of the tube, then the buckling occurs at the designated position and forms a convolution. In this paper, a forming apparatus is designed and developed to produce both discontinuous and continuous bellows of 304 stainless steel, and their characteristics are discussed respectively. Furthermore, the influences of process parameters and geometric parameters on the final convolution profile are deeply studied based on FEM analysis. The results suggest that the steel bellows fabricated by the presented buckling-induced forming method have a uniform shape and no obvious reduction of wall thickness. Meanwhile, the forming force required in the process is quite small.
A novel buckling-induced forming method is proposed to produce metal bellows. The tube billet is firstly treated by local heating and cooling, and the axial loading is applied on both ends of the tube, then the buckling occurs at the designated position and forms a convolution. In this paper, a forming apparatus is designed and developed to produce both discontinuous and continuous bellows of 304 stainless steel, and their characteristics are discussed respectively. Furthermore, the influences of process parameters and geometric parameters on the final convolution profile are deeply studied based on FEM analysis. The results suggest that the steel bellows fabricated by the presented buckling-induced forming method have a uniform shape and no obvious reduction of wall thickness. Meanwhile, the forming force required in the process is quite small.
2023, 36: 17.
doi: 10.1186/s10033-023-00841-5
Abstract:
Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers' requirements of product specification combinations. To better facilitate decision-making of modular product design, correlations among specifications and components originated from customers' conscious and subconscious preferences can be investigated by using big data on product sales. This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data. The correlations of the product specifications are determined by analyzing the collected product sales data. By building the relations between the product components and specifications, a matrix for measuring the correlation among product components is formed for component clustering. Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster. A case study of electric vehicles illustrates the application of the proposed method.
Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers' requirements of product specification combinations. To better facilitate decision-making of modular product design, correlations among specifications and components originated from customers' conscious and subconscious preferences can be investigated by using big data on product sales. This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data. The correlations of the product specifications are determined by analyzing the collected product sales data. By building the relations between the product components and specifications, a matrix for measuring the correlation among product components is formed for component clustering. Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster. A case study of electric vehicles illustrates the application of the proposed method.
2023, 36: 18.
doi: 10.1186/s10033-023-00849-x
Abstract:
With the further development of service-oriented, performance-based contracting (PBC) has been widely adopted in industry and manufacturing. However, maintenance optimization problems under PBC have not received enough attention. To further extend the scope of PBC's application in the field of maintenance optimization, we investigate the condition-based maintenance (CBM) optimization for gamma deteriorating systems under PBC. Considering the repairable single-component system subject to the gamma degradation process, this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC. In the proposed CBM model, the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate. Then, a particle swarm algorithm (PSO) and related solution procedure are presented to solve the multiple decision variables in our proposed model. In the end, a numerical example is provided so as to demonstrate the superiority of the presented model. By comparing the proposed policy with the conventional ones, the superiority of our proposed policy is proved, which can bring more profits to providers and improve performance. Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy. A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.
With the further development of service-oriented, performance-based contracting (PBC) has been widely adopted in industry and manufacturing. However, maintenance optimization problems under PBC have not received enough attention. To further extend the scope of PBC's application in the field of maintenance optimization, we investigate the condition-based maintenance (CBM) optimization for gamma deteriorating systems under PBC. Considering the repairable single-component system subject to the gamma degradation process, this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC. In the proposed CBM model, the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate. Then, a particle swarm algorithm (PSO) and related solution procedure are presented to solve the multiple decision variables in our proposed model. In the end, a numerical example is provided so as to demonstrate the superiority of the presented model. By comparing the proposed policy with the conventional ones, the superiority of our proposed policy is proved, which can bring more profits to providers and improve performance. Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy. A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.
2023, 36: 25.
doi: 10.1186/s10033-023-00842-4
Abstract:
Previous investigation on side channel pump mainly concentrates on parameter optimization and internal unsteady vortical flows. However, cavitation is prone to occur in a side channel pump, which is a challenging issue in promoting performance. In the present study, the cavitating flow is investigated numerically by the turbulence model of SAS combined with the Zwart cavitation model. The vapors inside the side channel pump firstly occur in the impeller passage near the inlet and then spread gradually to the downstream passages with the decrease of NPSHa. Moreover, a strong adverse pressure gradient is presented at the end of the cavity closure region, which leads to cavity shedding from the wall. The small scaled vortices in each passage reduce significantly and gather into larger vortices due to the cavitation. Comparing the three terms of vorticity transport equation with the vapor volume fraction and vorticity distributions, it is found that the stretching term is dominant and responsible for the vorticity production and evolution in cavitating flows. In addition, the magnitudes of the stretching term decrease once the cavitation occurs, while the values of dilatation are high in the cavity region and increase with the decreasing NPSHa. Even though the magnitude of the baroclinic torque term is smaller than vortex stretching and dilatation terms, it is important for the vorticity production along the cavity surface and near the cavity closure region. The pressure fluctuations in the impeller and side channel tend to be stronger due to the cavitation. The primary frequency of monitor points in the impeller is 24.94 Hz and in the side channel is 598.05 Hz. They are quite corresponding to the shaft frequency of 25 Hz (fshaft = 1/n = 25 Hz) and the blade frequency of 600 Hz (fblade = Z/n =600 Hz) respectively. This study complements the investigation on cavitation in the side channel pump, which could provide the theoretical foundation for further optimization of performance.
Previous investigation on side channel pump mainly concentrates on parameter optimization and internal unsteady vortical flows. However, cavitation is prone to occur in a side channel pump, which is a challenging issue in promoting performance. In the present study, the cavitating flow is investigated numerically by the turbulence model of SAS combined with the Zwart cavitation model. The vapors inside the side channel pump firstly occur in the impeller passage near the inlet and then spread gradually to the downstream passages with the decrease of NPSHa. Moreover, a strong adverse pressure gradient is presented at the end of the cavity closure region, which leads to cavity shedding from the wall. The small scaled vortices in each passage reduce significantly and gather into larger vortices due to the cavitation. Comparing the three terms of vorticity transport equation with the vapor volume fraction and vorticity distributions, it is found that the stretching term is dominant and responsible for the vorticity production and evolution in cavitating flows. In addition, the magnitudes of the stretching term decrease once the cavitation occurs, while the values of dilatation are high in the cavity region and increase with the decreasing NPSHa. Even though the magnitude of the baroclinic torque term is smaller than vortex stretching and dilatation terms, it is important for the vorticity production along the cavity surface and near the cavity closure region. The pressure fluctuations in the impeller and side channel tend to be stronger due to the cavitation. The primary frequency of monitor points in the impeller is 24.94 Hz and in the side channel is 598.05 Hz. They are quite corresponding to the shaft frequency of 25 Hz (fshaft = 1/n = 25 Hz) and the blade frequency of 600 Hz (fblade = Z/n =600 Hz) respectively. This study complements the investigation on cavitation in the side channel pump, which could provide the theoretical foundation for further optimization of performance.
2023, 36: 27.
doi: 10.1186/s10033-023-00853-1
Abstract:
Pinhole corrosion is difficult to discover through conventional ultrasonic guided waves inspection, particularly for micro-sized pinholes less than 1 mm in diameter. This study proposes a new micro-sized pinhole inspection method based on segmented time reversal (STR) and high-order modes cluster (HOMC) Lamb waves. First, the principle of defect echo enhancement using STR is introduced. Conventional and STR inspection experiments were conducted on aluminum plates with a thickness of 3 mm and defects with different diameters and depths. The parameters of the segment window are discussed in detail. The results indicate that the proposed method had an amplitude four times larger than of conventional ultrasonic guided waves inspection method for pinhole defect detection and could detect micro-sized pinhole defects as small as 0.5 mm in diameter and 0.5 mm in depth. Moreover, the segment window location and width (5−10 times width of the conventional excitation signal) did not affect the detection sensitivity. The combination of low-power and STR is more conducive to detection in different environments, indicating the robustness of the proposed method. Compared with conventional ultrasonic guided wave inspection methods, the proposed method can detect much smaller defect echoes usually obscured by noise that are difficult to detect with a lower excitation power and thus this study would be a good reference for pinhole defect detection.
Pinhole corrosion is difficult to discover through conventional ultrasonic guided waves inspection, particularly for micro-sized pinholes less than 1 mm in diameter. This study proposes a new micro-sized pinhole inspection method based on segmented time reversal (STR) and high-order modes cluster (HOMC) Lamb waves. First, the principle of defect echo enhancement using STR is introduced. Conventional and STR inspection experiments were conducted on aluminum plates with a thickness of 3 mm and defects with different diameters and depths. The parameters of the segment window are discussed in detail. The results indicate that the proposed method had an amplitude four times larger than of conventional ultrasonic guided waves inspection method for pinhole defect detection and could detect micro-sized pinhole defects as small as 0.5 mm in diameter and 0.5 mm in depth. Moreover, the segment window location and width (5−10 times width of the conventional excitation signal) did not affect the detection sensitivity. The combination of low-power and STR is more conducive to detection in different environments, indicating the robustness of the proposed method. Compared with conventional ultrasonic guided wave inspection methods, the proposed method can detect much smaller defect echoes usually obscured by noise that are difficult to detect with a lower excitation power and thus this study would be a good reference for pinhole defect detection.
2023, 36: 28.
doi: 10.1186/s10033-023-00831-7
Abstract:
Lubricating greases are widely used in e.g. open gear drives and gearboxes with difficult sealing conditions. The efficiency and heat balance of grease-lubricated gearboxes depend strongly on the lubrication mechanisms channeling and circulating, for which the grease flow is causal. The computational fluid dynamics opens up the possibility to visualize and understand the grease flow in gearboxes in more detail. In this study, a single-stage gearbox lubricated with an NLGI 1-2 grease was modeled by the finite-volume method to numerically investigate the fluid flow. Results show that the rotating gears influence the grease sump only locally around the gears. For a low grease fill volume, the rotation of the gears is widely separated from the grease sump. For a high grease fill volume, a pronounced gear-grease interaction results in a circulating grease flow around the gears. The simulated grease distributions show good accordance with high-speed camera recordings.
Lubricating greases are widely used in e.g. open gear drives and gearboxes with difficult sealing conditions. The efficiency and heat balance of grease-lubricated gearboxes depend strongly on the lubrication mechanisms channeling and circulating, for which the grease flow is causal. The computational fluid dynamics opens up the possibility to visualize and understand the grease flow in gearboxes in more detail. In this study, a single-stage gearbox lubricated with an NLGI 1-2 grease was modeled by the finite-volume method to numerically investigate the fluid flow. Results show that the rotating gears influence the grease sump only locally around the gears. For a low grease fill volume, the rotation of the gears is widely separated from the grease sump. For a high grease fill volume, a pronounced gear-grease interaction results in a circulating grease flow around the gears. The simulated grease distributions show good accordance with high-speed camera recordings.
2023, 36: 30.
doi: 10.1186/s10033-023-00847-z
Abstract:
The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the on-demand necessity to perform surgery during space missions. Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing. Among all 3D printing techniques, fused deposition modelling (FDM) is a low-cost and more rapid printing technique. This article proposes the fabrication of surgical instruments, namely, forceps and hemostat using the fused deposition modeling (FDM) process. Excellent mechanical properties are the only indicator to judge the quality of the functional parts. The mechanical properties of FDM-processed parts depend on various process parameters. These parameters are layer height, infill pattern, top/bottom pattern, number of top/bottom layers, infill density, flow, number of shells, printing temperature, build plate temperature, printing speed, and fan speed. Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid (PLA) parts printed by FDM. The experiments have performed through Taguchi's L27 orthogonal array (OA). Variance analysis (ANOVA) ascertains the significance of the process parameters and their percent contributions to the evaluation indexes. Finally, as a multi-objective optimization technique, grey relational analysis (GRA) obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties. Scanning electron microscopy (SEM) examines the types of defects and strong bonding between rasters. The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength (42.6 MPa) and modulus of elasticity (3274 MPa).
The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the on-demand necessity to perform surgery during space missions. Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing. Among all 3D printing techniques, fused deposition modelling (FDM) is a low-cost and more rapid printing technique. This article proposes the fabrication of surgical instruments, namely, forceps and hemostat using the fused deposition modeling (FDM) process. Excellent mechanical properties are the only indicator to judge the quality of the functional parts. The mechanical properties of FDM-processed parts depend on various process parameters. These parameters are layer height, infill pattern, top/bottom pattern, number of top/bottom layers, infill density, flow, number of shells, printing temperature, build plate temperature, printing speed, and fan speed. Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid (PLA) parts printed by FDM. The experiments have performed through Taguchi's L27 orthogonal array (OA). Variance analysis (ANOVA) ascertains the significance of the process parameters and their percent contributions to the evaluation indexes. Finally, as a multi-objective optimization technique, grey relational analysis (GRA) obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties. Scanning electron microscopy (SEM) examines the types of defects and strong bonding between rasters. The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength (42.6 MPa) and modulus of elasticity (3274 MPa).
2023, 36: 31.
doi: 10.1186/s10033-023-00855-z
Abstract:
The stress state is critical to the reliability of structures, but existing ultrasonic methods are challenging to measure local stress. In this paper, zero-group-velocity (ZGV) Lamb mode was proposed to measure the local stress field in thin aluminum plates. The Lamb wave's dispersive characteristics under initial stress were analyzed based on the Floquet-Bloch theory with Murnaghan hyperelastic material model. The obtained dispersion curves show that higher-order Lamb wave modes near the cut-off frequencies are sensitive to applied stress across the plate, indicating that the S1-ZGV mode has a rather high sensitivity to stress. Similar to conventional ultrasonic stress measurement, it is found that the frequency of the S1-ZGV mode changes near-linearly with the amplitude of applied stress. Numerical experiments were conducted to illustrate the feasibility of local stress measurement in a thin aluminum plate based on the S1-ZGV mode. Single and multiple localized stress fields were evaluated with the S1-ZGV method, and reconstructed results matched well with actual stress fields, proving that the ZGV Lamb wave method is a sensitive stress measurement technique in thin plates.
The stress state is critical to the reliability of structures, but existing ultrasonic methods are challenging to measure local stress. In this paper, zero-group-velocity (ZGV) Lamb mode was proposed to measure the local stress field in thin aluminum plates. The Lamb wave's dispersive characteristics under initial stress were analyzed based on the Floquet-Bloch theory with Murnaghan hyperelastic material model. The obtained dispersion curves show that higher-order Lamb wave modes near the cut-off frequencies are sensitive to applied stress across the plate, indicating that the S1-ZGV mode has a rather high sensitivity to stress. Similar to conventional ultrasonic stress measurement, it is found that the frequency of the S1-ZGV mode changes near-linearly with the amplitude of applied stress. Numerical experiments were conducted to illustrate the feasibility of local stress measurement in a thin aluminum plate based on the S1-ZGV mode. Single and multiple localized stress fields were evaluated with the S1-ZGV method, and reconstructed results matched well with actual stress fields, proving that the ZGV Lamb wave method is a sensitive stress measurement technique in thin plates.
2023, 36: 32.
doi: 10.1186/s10033-023-00863-z
Abstract:
Laser powder bed fusion (LPBF) is an advanced manufacturing technology; however, inappropriate LPBF process parameters may cause printing defects in materials. In the present work, the LPBF process of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy was investigated by a two-step optimization approach. Subsequently, heat transfer and liquid flow behaviors during LPBF were simulated by a well-tested phenomenological model, and the defect formation mechanisms in the as-fabricated alloy were discussed. The optimized process parameters for LPBF were detected as laser power changed from 195 W to 210 W, with scanning speed of 1250 mm/s. The LPBF process was divided into a laser irradiation stage, a spreading flow stage, and a solidification stage. The morphologies and defects of deposited tracks were affected by liquid flow behavior caused by rapid cooling rates. The findings of this research can provide valuable support for printing defect-free metal components.
Laser powder bed fusion (LPBF) is an advanced manufacturing technology; however, inappropriate LPBF process parameters may cause printing defects in materials. In the present work, the LPBF process of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy was investigated by a two-step optimization approach. Subsequently, heat transfer and liquid flow behaviors during LPBF were simulated by a well-tested phenomenological model, and the defect formation mechanisms in the as-fabricated alloy were discussed. The optimized process parameters for LPBF were detected as laser power changed from 195 W to 210 W, with scanning speed of 1250 mm/s. The LPBF process was divided into a laser irradiation stage, a spreading flow stage, and a solidification stage. The morphologies and defects of deposited tracks were affected by liquid flow behavior caused by rapid cooling rates. The findings of this research can provide valuable support for printing defect-free metal components.
2023, 36: 34.
doi: 10.1186/s10033-023-00857-x
Abstract:
This paper presents a cloud-based data-driven design optimization system, named DADOS, to help engineers and researchers improve a design or product easily and efficiently. DADOS has nearly 30 key algorithms, including the design of experiments, surrogate models, model validation and selection, prediction, optimization, and sensitivity analysis. Moreover, it also includes an exclusive ensemble surrogate modeling technique, the extended hybrid adaptive function, which can make use of the advantages of each surrogate and eliminate the effort of selecting the appropriate individual surrogate. To improve ease of use, DADOS provides a user-friendly graphical user interface and employed flow-based programming so that users can conduct design optimization just by dragging, dropping, and connecting algorithm blocks into a workflow instead of writing massive code. In addition, DADOS allows users to visualize the results to gain more insights into the design problems, allows multi-person collaborating on a project at the same time, and supports multi-disciplinary optimization. This paper also details the architecture and the user interface of DADOS. Two examples were employed to demonstrate how to use DADOS to conduct data-driven design optimization. Since DADOS is a cloud-based system, anyone can access DADOS atwww.dados.com.cn using their web browser without the need for installation or powerful hardware.
This paper presents a cloud-based data-driven design optimization system, named DADOS, to help engineers and researchers improve a design or product easily and efficiently. DADOS has nearly 30 key algorithms, including the design of experiments, surrogate models, model validation and selection, prediction, optimization, and sensitivity analysis. Moreover, it also includes an exclusive ensemble surrogate modeling technique, the extended hybrid adaptive function, which can make use of the advantages of each surrogate and eliminate the effort of selecting the appropriate individual surrogate. To improve ease of use, DADOS provides a user-friendly graphical user interface and employed flow-based programming so that users can conduct design optimization just by dragging, dropping, and connecting algorithm blocks into a workflow instead of writing massive code. In addition, DADOS allows users to visualize the results to gain more insights into the design problems, allows multi-person collaborating on a project at the same time, and supports multi-disciplinary optimization. This paper also details the architecture and the user interface of DADOS. Two examples were employed to demonstrate how to use DADOS to conduct data-driven design optimization. Since DADOS is a cloud-based system, anyone can access DADOS at
2023, 36: 35.
doi: 10.1186/s10033-023-00856-y
Abstract:
The crack fault is one of the most common faults in the rotor system, and researchers have paid close attention to its fault diagnosis. However, most studies focus on discussing the dynamic response characteristics caused by the crack rather than estimating the crack depth and position based on the obtained vibration signals. In this paper, a novel crack fault diagnosis and location method for a dual-disk hollow shaft rotor system based on the Radial basis function (RBF) network and Pattern recognition neural network (PRNN) is presented. Firstly, a rotor system model with a breathing crack suitable for a short-thick hollow shaft rotor is established based on the finite element method, where the crack's periodic opening and closing pattern and different degrees of crack depth are considered. Then, the dynamic response is obtained by the harmonic balance method. By adjusting the crack parameters, the dynamic characteristics related to the crack depth and position are analyzed through the amplitude-frequency responses and waterfall plots. The analysis results show that the first critical speed, first subcritical speed, first critical speed amplitude, and super-harmonic resonance peak at the first subcritical speed can be utilized for the crack fault diagnosis. Based on this, the RBF network and PRNN are adopted to determine the depth and approximate location of the crack respectively by taking the above dynamic characteristics as input. Test results show that the proposed method has high fault diagnosis accuracy. This research proposes a crack detection method adequate for the hollow shaft rotor system, where the crack depth and position are both unknown.
The crack fault is one of the most common faults in the rotor system, and researchers have paid close attention to its fault diagnosis. However, most studies focus on discussing the dynamic response characteristics caused by the crack rather than estimating the crack depth and position based on the obtained vibration signals. In this paper, a novel crack fault diagnosis and location method for a dual-disk hollow shaft rotor system based on the Radial basis function (RBF) network and Pattern recognition neural network (PRNN) is presented. Firstly, a rotor system model with a breathing crack suitable for a short-thick hollow shaft rotor is established based on the finite element method, where the crack's periodic opening and closing pattern and different degrees of crack depth are considered. Then, the dynamic response is obtained by the harmonic balance method. By adjusting the crack parameters, the dynamic characteristics related to the crack depth and position are analyzed through the amplitude-frequency responses and waterfall plots. The analysis results show that the first critical speed, first subcritical speed, first critical speed amplitude, and super-harmonic resonance peak at the first subcritical speed can be utilized for the crack fault diagnosis. Based on this, the RBF network and PRNN are adopted to determine the depth and approximate location of the crack respectively by taking the above dynamic characteristics as input. Test results show that the proposed method has high fault diagnosis accuracy. This research proposes a crack detection method adequate for the hollow shaft rotor system, where the crack depth and position are both unknown.
2023, 36: 36.
doi: 10.1186/s10033-023-00859-9
Abstract:
Vibration signals have the characteristics of multi-source strong shock coupling and strong noise interference owing to the complex structure of reciprocating machinery. Therefore, it is difficult to extract, analyze, and diagnose mechanical fault features. To accurately extract sensitive features from the strong noise interference and unsteady monitoring signals of reciprocating machinery, a study on the time-frequency feature extraction method of multi-source shock signals is conducted. Combining the characteristics of reciprocating mechanical vibration signals, a targeted optimization method considering the variational modal decomposition (VMD) mode number and second penalty factor is proposed, which completed the adaptive decomposition of coupled signals. Aiming at the bilateral asymmetric attenuation characteristics of reciprocating mechanical shock signals, a new bilateral adaptive Laplace wavelet (BALW) is established. A search strategy for wavelet local parameters of multi-shock signals is proposed using the harmony search (HS) method. A multi-source shock simulation signal is established, and actual data on the valve fault are obtained through diesel engine fault experiments. The fault recognition rate of the intake and exhaust valve clearance is above 90% and the extraction accuracy of the shock start position is improved by 10°.
Vibration signals have the characteristics of multi-source strong shock coupling and strong noise interference owing to the complex structure of reciprocating machinery. Therefore, it is difficult to extract, analyze, and diagnose mechanical fault features. To accurately extract sensitive features from the strong noise interference and unsteady monitoring signals of reciprocating machinery, a study on the time-frequency feature extraction method of multi-source shock signals is conducted. Combining the characteristics of reciprocating mechanical vibration signals, a targeted optimization method considering the variational modal decomposition (VMD) mode number and second penalty factor is proposed, which completed the adaptive decomposition of coupled signals. Aiming at the bilateral asymmetric attenuation characteristics of reciprocating mechanical shock signals, a new bilateral adaptive Laplace wavelet (BALW) is established. A search strategy for wavelet local parameters of multi-shock signals is proposed using the harmony search (HS) method. A multi-source shock simulation signal is established, and actual data on the valve fault are obtained through diesel engine fault experiments. The fault recognition rate of the intake and exhaust valve clearance is above 90% and the extraction accuracy of the shock start position is improved by 10°.
2023, 36: 37.
doi: 10.1186/s10033-023-00858-w
Abstract:
In recent years, the number of patients with orthopedic diseases such as cervical spondylosis has increased, resulting in an increase in the demand for orthopedic surgery. However, thermal necrosis and bone cracks caused by surgery severely restrict the development and progression of orthopedic surgery. For the material of cutting tool processing bone in bone surgery of drilling high temperature lead to cell death, easy to produce the problem such as crack cause secondary damage effects to restore, in this paper, a bionic drill was designed based on the micro-structure of the dung beetle's head and back. The microstructure configuration parameters were optimized by numerical analysis, and making use of the optical fiber laser marking machine preparation of bionic bit; through drilling test, the mathematical model of drilling temperature and crack generation based on micro-structure characteristic parameters was established by infrared thermal imaging technology and acoustic emission signal technology, and the cooling mechanism and crack suppression strategy were studied. The experimental results show that when the speed is 60 m/min, the cooling effects of the bionic bit T1 and T2 are 15.31% and 19.78%, respectively, and both kinds of bits show obvious crack suppression effect. The research in this paper provides a new idea for precision and efficient machining of bone materials, and the research results will help to improve the design and manufacturing technology and theoretical research level in the field of bone drilling tools.
In recent years, the number of patients with orthopedic diseases such as cervical spondylosis has increased, resulting in an increase in the demand for orthopedic surgery. However, thermal necrosis and bone cracks caused by surgery severely restrict the development and progression of orthopedic surgery. For the material of cutting tool processing bone in bone surgery of drilling high temperature lead to cell death, easy to produce the problem such as crack cause secondary damage effects to restore, in this paper, a bionic drill was designed based on the micro-structure of the dung beetle's head and back. The microstructure configuration parameters were optimized by numerical analysis, and making use of the optical fiber laser marking machine preparation of bionic bit; through drilling test, the mathematical model of drilling temperature and crack generation based on micro-structure characteristic parameters was established by infrared thermal imaging technology and acoustic emission signal technology, and the cooling mechanism and crack suppression strategy were studied. The experimental results show that when the speed is 60 m/min, the cooling effects of the bionic bit T1 and T2 are 15.31% and 19.78%, respectively, and both kinds of bits show obvious crack suppression effect. The research in this paper provides a new idea for precision and efficient machining of bone materials, and the research results will help to improve the design and manufacturing technology and theoretical research level in the field of bone drilling tools.
2023, 36: 38.
doi: 10.1186/s10033-023-00854-0
Abstract:
Complicated tribological behavior occurs when human fingers touch and perceive the surfaces of objects. In this process, people use their exploration style with different conditions, such as contact load, sliding speed, sliding direction, and angle of orientation between fingers and object surface consciously or unconsciously. This work addressed interlaboratory experimental devices for finger active and passive tactile friction analysis, showing two types of finger movement. In active sliding experiment, the participant slid their finger freely against the object surface, requiring the subject to control the motion conditions themselves. For passive sliding experiments, these motion conditions were adjusted by the device. Several analysis parameters, such as contact force, vibration acceleration signals, vibration magnitude, and fingerprint deformation were recorded simultaneously. Noticeable friction differences were observed when comparing active sliding and passive sliding. For passive sliding, stick-slip behavior occurred when sliding in the distal direction, evidenced by observing the friction force and the related deformation of the fingerprint ridges. The employed devices showed good repeatability and high reliability, which enriched the design of the experimental platform and provided guidance to the standardization research in the field of tactile friction.
Complicated tribological behavior occurs when human fingers touch and perceive the surfaces of objects. In this process, people use their exploration style with different conditions, such as contact load, sliding speed, sliding direction, and angle of orientation between fingers and object surface consciously or unconsciously. This work addressed interlaboratory experimental devices for finger active and passive tactile friction analysis, showing two types of finger movement. In active sliding experiment, the participant slid their finger freely against the object surface, requiring the subject to control the motion conditions themselves. For passive sliding experiments, these motion conditions were adjusted by the device. Several analysis parameters, such as contact force, vibration acceleration signals, vibration magnitude, and fingerprint deformation were recorded simultaneously. Noticeable friction differences were observed when comparing active sliding and passive sliding. For passive sliding, stick-slip behavior occurred when sliding in the distal direction, evidenced by observing the friction force and the related deformation of the fingerprint ridges. The employed devices showed good repeatability and high reliability, which enriched the design of the experimental platform and provided guidance to the standardization research in the field of tactile friction.
2023, 36: 41.
doi: 10.1186/s10033-023-00840-6
Abstract:
In current research, many researchers propose analytical expressions for calculating the packing structure of spherical particles such as DN Model, Compact Model and NLS criterion et al. However, there is still a question that has not been well explained yet. That is: What is the core factors affecting the thermal conductivity of particles? In this paper, based on the coupled discrete element-finite difference (DE-FD) method and spherical aluminum powder, the relationship between the parameters and the thermal conductivity of the powder (ETCp) is studied. It is found that the key factor that can described the change trend of ETCp more accurately is not the materials of the powder but the average contact area between particles (aave) which also have a close nonlinear relationship with the average particle size d50. Based on this results, the expression for calculating the ETCp of the sphere metal powder is successfully reduced to only one main parameter d50 and an efficient calculation model is proposed which can applicate both in room and high temperature and the corresponding error is less than 20.9% in room temperature. Therefore, in this study, based on the core factors analyzation, a fast calculation model of ETCp is proposed, which has a certain guiding significance in the field of thermal field simulation.
In current research, many researchers propose analytical expressions for calculating the packing structure of spherical particles such as DN Model, Compact Model and NLS criterion et al. However, there is still a question that has not been well explained yet. That is: What is the core factors affecting the thermal conductivity of particles? In this paper, based on the coupled discrete element-finite difference (DE-FD) method and spherical aluminum powder, the relationship between the parameters and the thermal conductivity of the powder (ETCp) is studied. It is found that the key factor that can described the change trend of ETCp more accurately is not the materials of the powder but the average contact area between particles (aave) which also have a close nonlinear relationship with the average particle size d50. Based on this results, the expression for calculating the ETCp of the sphere metal powder is successfully reduced to only one main parameter d50 and an efficient calculation model is proposed which can applicate both in room and high temperature and the corresponding error is less than 20.9% in room temperature. Therefore, in this study, based on the core factors analyzation, a fast calculation model of ETCp is proposed, which has a certain guiding significance in the field of thermal field simulation.
2023, 36: 44.
doi: 10.1186/s10033-023-00870-0
Abstract:
Assembly geometric error as a part of the machine tool system errors has a significant influence on the machining accuracy of the multi-axis machine tool. And it cannot be eliminated due to the error propagation of components in the assembly process, which is generally non-uniformly distributed in the whole working space. A comprehensive expression model for assembly geometric error is greatly helpful for machining quality control of machine tools to meet the demand for machining accuracy in practice. However, the expression ranges based on the standard quasi-static expression model for assembly geometric errors are far less than those needed in the whole working space of the multi-axis machine tool. To address this issue, a modeling methodology based on the Jacobian-Torsor model is proposed to describe the spatially distributed geometric errors. Firstly, an improved kinematic Jacobian-Torsor model is developed to describe the relative movements such as translation and rotation motion between assembly bodies, respectively. Furthermore, based on the proposed kinematic Jacobian-Torsor model, a spatial expression of geometric errors for the multi-axis machine tool is given. And simulation and experimental verification are taken with the investigation of the spatial distribution of geometric errors on five four-axis machine tools. The results validate the effectiveness of the proposed kinematic Jacobian-Torsor model in dealing with the spatial expression of assembly geometric errors.
Assembly geometric error as a part of the machine tool system errors has a significant influence on the machining accuracy of the multi-axis machine tool. And it cannot be eliminated due to the error propagation of components in the assembly process, which is generally non-uniformly distributed in the whole working space. A comprehensive expression model for assembly geometric error is greatly helpful for machining quality control of machine tools to meet the demand for machining accuracy in practice. However, the expression ranges based on the standard quasi-static expression model for assembly geometric errors are far less than those needed in the whole working space of the multi-axis machine tool. To address this issue, a modeling methodology based on the Jacobian-Torsor model is proposed to describe the spatially distributed geometric errors. Firstly, an improved kinematic Jacobian-Torsor model is developed to describe the relative movements such as translation and rotation motion between assembly bodies, respectively. Furthermore, based on the proposed kinematic Jacobian-Torsor model, a spatial expression of geometric errors for the multi-axis machine tool is given. And simulation and experimental verification are taken with the investigation of the spatial distribution of geometric errors on five four-axis machine tools. The results validate the effectiveness of the proposed kinematic Jacobian-Torsor model in dealing with the spatial expression of assembly geometric errors.
2023, 36: 46.
doi: 10.1186/s10033-023-00877-7
Abstract:
To enrich material types applied to additive manufacturing and enlarge application scope of additive manufacturing in conformal cooling tools, M2 high-speed steel specimens were fabricated by selective laser melting (SLM). Effects of SLM parameters on the microstructure and mechanical properties of M2 high-speed steel were investigated. The results showed that substrate temperature and energy density had significant influence on the densification process of materials and defects control. Models to evaluate the effect of substrate temperature and energy density on hardness were studied. The optimized process parameters, laser power, scan speed, scan distance, and substrate temperature, for fabricated M2 are 220 W, 960 mm/s, 0.06 mm, and 200 ℃, respectively. Based on this, the hardness and tensile strength reached 60 HRC and 1000 MPa, respectively. Interlaminar crack formation and suppression mechanism and the relationship between temperature gradient and thermal stress were illustrated. The inhibition effect of substrate temperature on the cracks generated by residual stresses was also explained. AM showed great application potential in the field of special conformal cooling cutting tool preparation.
To enrich material types applied to additive manufacturing and enlarge application scope of additive manufacturing in conformal cooling tools, M2 high-speed steel specimens were fabricated by selective laser melting (SLM). Effects of SLM parameters on the microstructure and mechanical properties of M2 high-speed steel were investigated. The results showed that substrate temperature and energy density had significant influence on the densification process of materials and defects control. Models to evaluate the effect of substrate temperature and energy density on hardness were studied. The optimized process parameters, laser power, scan speed, scan distance, and substrate temperature, for fabricated M2 are 220 W, 960 mm/s, 0.06 mm, and 200 ℃, respectively. Based on this, the hardness and tensile strength reached 60 HRC and 1000 MPa, respectively. Interlaminar crack formation and suppression mechanism and the relationship between temperature gradient and thermal stress were illustrated. The inhibition effect of substrate temperature on the cracks generated by residual stresses was also explained. AM showed great application potential in the field of special conformal cooling cutting tool preparation.
2023, 36: 49.
doi: 10.1186/s10033-023-00866-w
Abstract:
Bolt connection is one of the main fixing methods of cylindrical shell structures. A typical bolted connection model is considered as a tuned system. However, in the actual working conditions, due to the manufacturing error, installation error and uneven materials of bolts, there are always random errors between different bolts. To investigate the influence of non-uniform parameters of bolt joint, including the stiffness and the distribution position, on frequency complexity characteristics of cylindrical shell through a statistical method is the main aim of this paper. The bolted joints considered here were simplified as a series of springs with random features. The vibration equation of the bolted joined cylindrical shell was derived based on Sanders' thin shell theory. The Monte Carlo simulation and statistical theory were applied to the statistical analysis of mode characteristics of the system. First, the frequency and mode shape of the tuned system were investigated and compared with FEM. Then, the effect of the random distribution and the random constraint stiffness of the bolts on the frequency and mode shape were studied. And the statistical analysis on the natural frequencies was evaluated for different mistuned levels. And some special cases were presented to help understand the effect of random mistuning. This research introduces random theory into the modeling of bolted joints and proposes a reference result to interpret the complexity of the modal characteristics of cylindrical shells with non-uniform parameters of bolt joints.
Bolt connection is one of the main fixing methods of cylindrical shell structures. A typical bolted connection model is considered as a tuned system. However, in the actual working conditions, due to the manufacturing error, installation error and uneven materials of bolts, there are always random errors between different bolts. To investigate the influence of non-uniform parameters of bolt joint, including the stiffness and the distribution position, on frequency complexity characteristics of cylindrical shell through a statistical method is the main aim of this paper. The bolted joints considered here were simplified as a series of springs with random features. The vibration equation of the bolted joined cylindrical shell was derived based on Sanders' thin shell theory. The Monte Carlo simulation and statistical theory were applied to the statistical analysis of mode characteristics of the system. First, the frequency and mode shape of the tuned system were investigated and compared with FEM. Then, the effect of the random distribution and the random constraint stiffness of the bolts on the frequency and mode shape were studied. And the statistical analysis on the natural frequencies was evaluated for different mistuned levels. And some special cases were presented to help understand the effect of random mistuning. This research introduces random theory into the modeling of bolted joints and proposes a reference result to interpret the complexity of the modal characteristics of cylindrical shells with non-uniform parameters of bolt joints.
2023, 36: 50.
doi: 10.1186/s10033-023-00874-w
Abstract:
The judgment of gear failure is based on the pitting area ratio of gear. Traditional gear pitting calculation method mainly rely on manual visual inspection. This method is greatly affected by human factors, and is greatly affected by the working experience, training degree and fatigue degree of the detection personnel, so the detection results may be biased. The non-contact computer vision measurement can carry out non-destructive testing and monitoring under the working condition of the machine, and has high detection accuracy. To improve the measurement accuracy of gear pitting, a novel multi-scale splicing attention U-Net (MSSA U-Net) is explored in this study. An image splicing module is first proposed for concatenating the output feature maps of multiple convolutional layers into a splicing feature map with more semantic information. Then, an attention module is applied to select the key features of the splicing feature map. Given that MSSA U-Net adequately uses multi-scale semantic features, it has better segmentation performance on irregular small objects than U-Net and attention U-Net. On the basis of the designed visual detection platform and MSSA U-Net, a methodology for measuring the area ratio of gear pitting is proposed. With three datasets, experimental results show that MSSA U-Net is superior to existing typical image segmentation methods and can accurately segment different levels of pitting due to its strong segmentation ability. Therefore, the proposed methodology can be effectively applied in measuring the pitting area ratio and determining the level of gear pitting.
The judgment of gear failure is based on the pitting area ratio of gear. Traditional gear pitting calculation method mainly rely on manual visual inspection. This method is greatly affected by human factors, and is greatly affected by the working experience, training degree and fatigue degree of the detection personnel, so the detection results may be biased. The non-contact computer vision measurement can carry out non-destructive testing and monitoring under the working condition of the machine, and has high detection accuracy. To improve the measurement accuracy of gear pitting, a novel multi-scale splicing attention U-Net (MSSA U-Net) is explored in this study. An image splicing module is first proposed for concatenating the output feature maps of multiple convolutional layers into a splicing feature map with more semantic information. Then, an attention module is applied to select the key features of the splicing feature map. Given that MSSA U-Net adequately uses multi-scale semantic features, it has better segmentation performance on irregular small objects than U-Net and attention U-Net. On the basis of the designed visual detection platform and MSSA U-Net, a methodology for measuring the area ratio of gear pitting is proposed. With three datasets, experimental results show that MSSA U-Net is superior to existing typical image segmentation methods and can accurately segment different levels of pitting due to its strong segmentation ability. Therefore, the proposed methodology can be effectively applied in measuring the pitting area ratio and determining the level of gear pitting.
2023, 36: 51.
doi: 10.1186/s10033-023-00867-9
Abstract:
Periodic components are of great significance for fault diagnosis and health monitoring of rotating machinery. Time synchronous averaging is an effective and convenient technique for extracting those components. However, the performance of time synchronous averaging is seriously limited when the separate segments are poorly synchronized. This paper proposes a new averaging method capable of extracting periodic components without external reference and an accurate period to solve this problem. With this approach, phase detection and compensation eliminate all segments' phase differences, which enables the segments to be well synchronized. The effectiveness of the proposed method is validated by numerical and experimental signals.
Periodic components are of great significance for fault diagnosis and health monitoring of rotating machinery. Time synchronous averaging is an effective and convenient technique for extracting those components. However, the performance of time synchronous averaging is seriously limited when the separate segments are poorly synchronized. This paper proposes a new averaging method capable of extracting periodic components without external reference and an accurate period to solve this problem. With this approach, phase detection and compensation eliminate all segments' phase differences, which enables the segments to be well synchronized. The effectiveness of the proposed method is validated by numerical and experimental signals.
2023, 36: 52.
doi: 10.1186/s10033-023-00879-5
Abstract:
To benefit tissue removal and postoperative rehabilitation, increased efficiency and accuracy and reduced operating force are strongly required in the osteotomy. A novel elliptical vibration cutting (EVC) has been introduced for bone cutting compared with conventional cutting (CC) in this paper. With the assistance of high-speed microscope imaging and the dynamometer, the material removals of cortical bone and their cutting forces from two cutting regimes were recorded and analysed comprehensively, which clearly demonstrated the chip morphology improvement and the average cutting force reduction in the EVC process. It also revealed that the elliptical vibration of the cutting tool could promote fracture propagation along the shear direction. These new findings will be of important theoretical and practical values to apply the innovative EVC process to the surgical procedures of the osteotomy.
To benefit tissue removal and postoperative rehabilitation, increased efficiency and accuracy and reduced operating force are strongly required in the osteotomy. A novel elliptical vibration cutting (EVC) has been introduced for bone cutting compared with conventional cutting (CC) in this paper. With the assistance of high-speed microscope imaging and the dynamometer, the material removals of cortical bone and their cutting forces from two cutting regimes were recorded and analysed comprehensively, which clearly demonstrated the chip morphology improvement and the average cutting force reduction in the EVC process. It also revealed that the elliptical vibration of the cutting tool could promote fracture propagation along the shear direction. These new findings will be of important theoretical and practical values to apply the innovative EVC process to the surgical procedures of the osteotomy.
2023, 36: 57.
doi: 10.1186/s10033-023-00887-5
Abstract:
Titanium alloy has been applied in the field of aerospace manufacturing for its high specific strength and hardness. Nonetheless, these properties also cause general problems in the machining, such as processing inefficiency, serious wear, poor workpiece face quality, etc. Aiming at the above problems, this paper carried out a comparative experimental study on titanium alloy milling based on the CAMC and BEMC. The variation law of cutting force and wear morphology of the two tools were obtained, and the wear mechanism and the effect of wear on machining quality were analyzed. The conclusion is that in contrast with BEMC, under the action of cutting thickness thinning mechanism, the force of CAMC was less, and its fluctuation was more stable. The flank wear was uniform and near the cutting edge, and the wear rate was slower. In the early period, the wear mechanism of CAMC was mainly adhesion. Gradually, oxidative wear also occurred with milling. Furthermore, the surface residual height of CAMC was lower. There is no obvious peak and trough accompanied by fewer surface defects.
Titanium alloy has been applied in the field of aerospace manufacturing for its high specific strength and hardness. Nonetheless, these properties also cause general problems in the machining, such as processing inefficiency, serious wear, poor workpiece face quality, etc. Aiming at the above problems, this paper carried out a comparative experimental study on titanium alloy milling based on the CAMC and BEMC. The variation law of cutting force and wear morphology of the two tools were obtained, and the wear mechanism and the effect of wear on machining quality were analyzed. The conclusion is that in contrast with BEMC, under the action of cutting thickness thinning mechanism, the force of CAMC was less, and its fluctuation was more stable. The flank wear was uniform and near the cutting edge, and the wear rate was slower. In the early period, the wear mechanism of CAMC was mainly adhesion. Gradually, oxidative wear also occurred with milling. Furthermore, the surface residual height of CAMC was lower. There is no obvious peak and trough accompanied by fewer surface defects.
2023, 36: 61.
doi: 10.1186/s10033-023-00889-3
Abstract:
Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions (EOC), which are inevitable in the normal inspection of civil and mechanical structures. This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network (1D-CNN). After singular value decomposition-based feature extraction processing, a temporal robust damage index (TRDI) is extracted, and the effect of EOCs is well removed. Hence, even for the signals with a very large temperature-varying range and low signal-to-noise ratios (SNRs), the final damage detection and localization accuracy retain perfect 100%. Verifications are conducted on two different experimental datasets. The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises, and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20℃ to 60℃. It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly, showing great potential for application in complex and unknown EOC.
Ultrasonic guided wave is an attractive monitoring technique for large-scale structures but is vulnerable to changes in environmental and operational conditions (EOC), which are inevitable in the normal inspection of civil and mechanical structures. This paper thus presents a robust guided wave-based method for damage detection and localization under complex environmental conditions by singular value decomposition-based feature extraction and one-dimensional convolutional neural network (1D-CNN). After singular value decomposition-based feature extraction processing, a temporal robust damage index (TRDI) is extracted, and the effect of EOCs is well removed. Hence, even for the signals with a very large temperature-varying range and low signal-to-noise ratios (SNRs), the final damage detection and localization accuracy retain perfect 100%. Verifications are conducted on two different experimental datasets. The first dataset consists of guided wave signals collected from a thin aluminum plate with artificial noises, and the second is a publicly available experimental dataset of guided wave signals acquired on a composite plate with a temperature ranging from 20℃ to 60℃. It is demonstrated that the proposed method can detect and localize the damage accurately and rapidly, showing great potential for application in complex and unknown EOC.
2023, 36: 63.
doi: 10.1186/s10033-023-00884-8
Abstract:
Spacecraft pose estimation is an important technology to maintain or change the spacecraft orientation in space. For spacecraft pose estimation, when two spacecraft are relatively distant, the depth information of the space point is less than that of the measuring distance, so the camera model can be seen as a weak perspective projection model. In this paper, a spacecraft pose estimation algorithm based on four symmetrical points of the spacecraft outline is proposed. The analytical solution of the spacecraft pose is obtained by solving the weak perspective projection model, which can satisfy the requirements of the measurement model when the measurement distance is long. The optimal solution is obtained from the weak perspective projection model to the perspective projection model, which can meet the measurement requirements when the measuring distance is small. The simulation results show that the proposed algorithm can obtain better results, even though the noise is large.
Spacecraft pose estimation is an important technology to maintain or change the spacecraft orientation in space. For spacecraft pose estimation, when two spacecraft are relatively distant, the depth information of the space point is less than that of the measuring distance, so the camera model can be seen as a weak perspective projection model. In this paper, a spacecraft pose estimation algorithm based on four symmetrical points of the spacecraft outline is proposed. The analytical solution of the spacecraft pose is obtained by solving the weak perspective projection model, which can satisfy the requirements of the measurement model when the measurement distance is long. The optimal solution is obtained from the weak perspective projection model to the perspective projection model, which can meet the measurement requirements when the measuring distance is small. The simulation results show that the proposed algorithm can obtain better results, even though the noise is large.
2023, 36: 66.
doi: 10.1186/s10033-023-00890-w
Abstract:
Cavitation generation methods have been used in multifarious directions because of their diversity, and numerous studies and discussions have been conducted on cavitation generation methods. This study aims to explore the generating mechanism and evolution law of volume alternate cavitation (VAC). In the VAC, liquid water is placed in an airtight container with a variable volume. As the volume alternately changes, the liquid water inside the container continues to cavitate. Then, the mixture turbulence model and in-cylinder dynamic grid model are adopted to conduct computational fluid dynamics simulation of volume alternate cavitation. In the simulation, the cloud images at seven heights on the central axis are monitored, and the phenomenon and mechanism of height and eccentricity are analyzed in detail. By employing the cavitation flow visualization method, the generating mechanism and evolution law of cavitation are revealed. The synergistic effects of experiments and high-speed camera capturing confirm the correctness of the simulation results. In the experiment, the volume change stroke of the airtight container is set to 20 mm, the volume change frequency is 18 Hz, and the shooting frequency of the high-speed camera is set to 10000 FPS. The experimental results indicate that the position of the cavitation phenomenon has a reasonable law during the whole evolution cycle of the cavitation cloud. Also, the volume alternation cycle corresponds to the generation, development, and collapse stages of cavitation bubbles.
Cavitation generation methods have been used in multifarious directions because of their diversity, and numerous studies and discussions have been conducted on cavitation generation methods. This study aims to explore the generating mechanism and evolution law of volume alternate cavitation (VAC). In the VAC, liquid water is placed in an airtight container with a variable volume. As the volume alternately changes, the liquid water inside the container continues to cavitate. Then, the mixture turbulence model and in-cylinder dynamic grid model are adopted to conduct computational fluid dynamics simulation of volume alternate cavitation. In the simulation, the cloud images at seven heights on the central axis are monitored, and the phenomenon and mechanism of height and eccentricity are analyzed in detail. By employing the cavitation flow visualization method, the generating mechanism and evolution law of cavitation are revealed. The synergistic effects of experiments and high-speed camera capturing confirm the correctness of the simulation results. In the experiment, the volume change stroke of the airtight container is set to 20 mm, the volume change frequency is 18 Hz, and the shooting frequency of the high-speed camera is set to 10000 FPS. The experimental results indicate that the position of the cavitation phenomenon has a reasonable law during the whole evolution cycle of the cavitation cloud. Also, the volume alternation cycle corresponds to the generation, development, and collapse stages of cavitation bubbles.
2023, 36: 69.
doi: 10.1186/s10033-023-00900-x
Abstract:
Aero-engine fan blades often use a cavity structure to improve the thrust-to-weight ratio of the aircraft. However, the use of the cavity structure brings a series of difficulties to the manufacturing and processing of the blades. Due to the limitation of blade manufacturing technology, it is difficult for the internal cavity structure to achieve the designed contour shape, so the blade has uneven wall thickness and poor consistency, which affects the fatigue performance and airflow dynamic performance of the blade. In order to reduce the influence of uneven wall thickness, this paper proposes a grinding allowance extraction method considering the double dimension constraints (DDC) of the inner and outer contours of the hollow blade. Constrain the two dimensions of the inner and outer contours of the hollow blade. On the premise of satisfying the outer contour constraints, the machining model of the blade is modified according to the distribution of the inwall contour to obtain a more reasonable distribution of the grinding allowance. On the premise of satisfying the contour constraints, according to the distribution of the inwall contour, the machining model of the blade is modified to obtain a more reasonable distribution of the grinding allowance. Through the grinding experiment of the hollow blade, the surface roughness is below Ra0.4 μm, and the contour accuracy is between − 0.05~0.14 mm, which meets the processing requirements. Compared with the allowance extraction method that only considers the contour, the problem of poor wall thickness consistency can be effectively improved. It can be used to extract the allowance of aero-engine blades with hollow features, which lays a foundation for the study of hollow blade grinding methods with high service performance.
Aero-engine fan blades often use a cavity structure to improve the thrust-to-weight ratio of the aircraft. However, the use of the cavity structure brings a series of difficulties to the manufacturing and processing of the blades. Due to the limitation of blade manufacturing technology, it is difficult for the internal cavity structure to achieve the designed contour shape, so the blade has uneven wall thickness and poor consistency, which affects the fatigue performance and airflow dynamic performance of the blade. In order to reduce the influence of uneven wall thickness, this paper proposes a grinding allowance extraction method considering the double dimension constraints (DDC) of the inner and outer contours of the hollow blade. Constrain the two dimensions of the inner and outer contours of the hollow blade. On the premise of satisfying the outer contour constraints, the machining model of the blade is modified according to the distribution of the inwall contour to obtain a more reasonable distribution of the grinding allowance. On the premise of satisfying the contour constraints, according to the distribution of the inwall contour, the machining model of the blade is modified to obtain a more reasonable distribution of the grinding allowance. Through the grinding experiment of the hollow blade, the surface roughness is below Ra0.4 μm, and the contour accuracy is between − 0.05~0.14 mm, which meets the processing requirements. Compared with the allowance extraction method that only considers the contour, the problem of poor wall thickness consistency can be effectively improved. It can be used to extract the allowance of aero-engine blades with hollow features, which lays a foundation for the study of hollow blade grinding methods with high service performance.
2023, 36: 70.
doi: 10.1186/s10033-023-00888-4
Abstract:
The operation of a shield tunnel boring machine (TBM) in a high-strength hard rock stratum results in significant cutter damage, adversely affecting the thrust and torque of the cutter head. Therefore, it is very important to carry out the research on the stress characteristics and optimize the cutter parameters of cutters break high-strength hard rock. In this paper, the rock-breaking performance of cutters in an andesite stratum in the tunnel of Qingdao Metro Line No. 8 was investigated using the discrete element method and theoretical analysis. The rock-breaking processes of a disc cutter and wedge tooth cutter were simulated by software particle flow code PFC3D, and the rock-breaking degree, stress of the cutter, and rock-breaking specific energy were analyzed. The rock damage caused by the cutter in a specific section was divided into three stages: the advanced influence, crushing, and stabilizing stages. The rock-breaking degree and the tangential and normal forces of the wedge tooth cutter are larger than that of the disc cutter under the same conditions. The disc cutter (wedge tooth cutter) has the highest rock-breaking efficiency at a cutter spacing of 100 mm (110 mm) and a penetration depth of 8 mm (10 mm), and the rock-breaking specific energy is 11.48 MJ/m3 (12.05 MJ/m3). Therefore, two types of cutters with different penetration depths or cutter spacing should be considered. The number of teeth of wedge tooth cutters can be increased in hard strata to improve the rock-breaking efficiency of the shield. The research results provide a reference for shield cutterhead selection and cutter layout in similar projects.
The operation of a shield tunnel boring machine (TBM) in a high-strength hard rock stratum results in significant cutter damage, adversely affecting the thrust and torque of the cutter head. Therefore, it is very important to carry out the research on the stress characteristics and optimize the cutter parameters of cutters break high-strength hard rock. In this paper, the rock-breaking performance of cutters in an andesite stratum in the tunnel of Qingdao Metro Line No. 8 was investigated using the discrete element method and theoretical analysis. The rock-breaking processes of a disc cutter and wedge tooth cutter were simulated by software particle flow code PFC3D, and the rock-breaking degree, stress of the cutter, and rock-breaking specific energy were analyzed. The rock damage caused by the cutter in a specific section was divided into three stages: the advanced influence, crushing, and stabilizing stages. The rock-breaking degree and the tangential and normal forces of the wedge tooth cutter are larger than that of the disc cutter under the same conditions. The disc cutter (wedge tooth cutter) has the highest rock-breaking efficiency at a cutter spacing of 100 mm (110 mm) and a penetration depth of 8 mm (10 mm), and the rock-breaking specific energy is 11.48 MJ/m3 (12.05 MJ/m3). Therefore, two types of cutters with different penetration depths or cutter spacing should be considered. The number of teeth of wedge tooth cutters can be increased in hard strata to improve the rock-breaking efficiency of the shield. The research results provide a reference for shield cutterhead selection and cutter layout in similar projects.
2023, 36: 71.
doi: 10.1186/s10033-023-00896-4
Abstract:
Continuously variable transmission (CVT) of noncircular gear has the technical advantages of large bearing capacity and high transmission efficiency. The key technology of CVT with noncircular gear has been broken through some countries, and is in the stage of deep application research. Although the characteristics and design methods of noncircular gear pairs have been continuously studied in China, the noncircular gear CVT is still in the preliminary exploration and research stage. The linear functional noncircular gear pair, whose transmission ratio is a linear function in the working section, to realize continuously variable transmission was the research object in this paper. According to the required transmission ratio in the working section, the transmission ratio function in the non-working section was constructed by using a polynomial. And then the influence of pitch curve parameters in the working section on which in the non-working section was also analyzed to obtain the pitch curve suitable for transmission of this gear pair. In addition, for improving the stability and bearing capacity of gear transmission, the noncircular gear pair transmission with high contact ratio was designed. Furthermore, the accurate value of the contact tooth length was calculated based on the gear principle and the characteristics of the involute tooth profile, from this the contact tooth length error was calculated by comparing the accurate value with its actual value obtained by the rolling experiment. Finally, an indirect method to verify the contact ratio by detecting the contact length error of the tooth profile was proposed.
Continuously variable transmission (CVT) of noncircular gear has the technical advantages of large bearing capacity and high transmission efficiency. The key technology of CVT with noncircular gear has been broken through some countries, and is in the stage of deep application research. Although the characteristics and design methods of noncircular gear pairs have been continuously studied in China, the noncircular gear CVT is still in the preliminary exploration and research stage. The linear functional noncircular gear pair, whose transmission ratio is a linear function in the working section, to realize continuously variable transmission was the research object in this paper. According to the required transmission ratio in the working section, the transmission ratio function in the non-working section was constructed by using a polynomial. And then the influence of pitch curve parameters in the working section on which in the non-working section was also analyzed to obtain the pitch curve suitable for transmission of this gear pair. In addition, for improving the stability and bearing capacity of gear transmission, the noncircular gear pair transmission with high contact ratio was designed. Furthermore, the accurate value of the contact tooth length was calculated based on the gear principle and the characteristics of the involute tooth profile, from this the contact tooth length error was calculated by comparing the accurate value with its actual value obtained by the rolling experiment. Finally, an indirect method to verify the contact ratio by detecting the contact length error of the tooth profile was proposed.
2023, 36: 84.
doi: 10.1186/s10033-023-00915-4
Abstract:
Pressure fluctuation due to rotor-stator interaction in turbomachinery is unavoidable, inducing strong vibration in the equipment and shortening its lifecycle. The investigation of optimization methods for an industrial centrifugal pump was carried out to reduce the intensity of pressure fluctuation to extend the lifecycle of these devices. Considering the time-consuming transient simulation of unsteady pressure, a novel optimization strategy was proposed by discretizing design variables and genetic algorithm. Four highly related design parameters were chosen, and 40 transient sample cases were generated and simulated using an automatic program. 70% of them were used for training the surrogate model, and the others were for verifying the accuracy of the surrogate model. Furthermore, a modified discrete genetic algorithm (MDGA) was proposed to reduce the optimization cost owing to transient numerical simulation. For the benchmark test, the proposed MDGA showed a great advantage over the original genetic algorithm regarding searching speed and effectively dealt with the discrete variables by dramatically increasing the convergence rate. After optimization, the performance and stability of the inline pump were improved. The efficiency increased by more than 2.2%, and the pressure fluctuation intensity decreased by more than 20% under design condition. This research proposed an optimization method for reducing discrete transient characteristics in centrifugal pumps.
Pressure fluctuation due to rotor-stator interaction in turbomachinery is unavoidable, inducing strong vibration in the equipment and shortening its lifecycle. The investigation of optimization methods for an industrial centrifugal pump was carried out to reduce the intensity of pressure fluctuation to extend the lifecycle of these devices. Considering the time-consuming transient simulation of unsteady pressure, a novel optimization strategy was proposed by discretizing design variables and genetic algorithm. Four highly related design parameters were chosen, and 40 transient sample cases were generated and simulated using an automatic program. 70% of them were used for training the surrogate model, and the others were for verifying the accuracy of the surrogate model. Furthermore, a modified discrete genetic algorithm (MDGA) was proposed to reduce the optimization cost owing to transient numerical simulation. For the benchmark test, the proposed MDGA showed a great advantage over the original genetic algorithm regarding searching speed and effectively dealt with the discrete variables by dramatically increasing the convergence rate. After optimization, the performance and stability of the inline pump were improved. The efficiency increased by more than 2.2%, and the pressure fluctuation intensity decreased by more than 20% under design condition. This research proposed an optimization method for reducing discrete transient characteristics in centrifugal pumps.
2023, 36: 85.
doi: 10.1186/s10033-023-00922-5
Abstract:
Current research on pilot-operated relief valve stability is primarily conducted from the perspective of system dynamics or stability criteria, and most of the existing conclusions focus on the spool shape, damping hole size, and pulsation frequency of the pump. However, the essential factors pertaining to the unstable vibration of relief valves remain ambiguous. In this study, the dynamic behavior of a pilot-operated relief valve is investigated using the frequency-domain method. The result suggests that the dynamic pressure feedback orifice is vital to the dynamic characteristics of the valve. A large orifice has a low flow resistance. In this case, the fluid in the main spring chamber flows freely, which is not conducive to the stability of the relief valve. However, a small orifice may create significant flow resistance, thus restricting fluid flow. In this case, the oil inside the main valve spring chamber is equivalent to a high-stiffness liquid spring. The main mass–spring vibration system has a natural frequency that differs significantly from the operating frequency of the relief valve, which is conducive to the stability of the relief valve. Good agreement is obtained between the theoretical analysis and experiments. The results indicate that designing a dynamic pressure feedback orifice of an appropriate size is beneficial to improving the stability of hydraulic pilot-operated relief valves. In addition, the dynamic pressure feedback orifice reduces the response speed of the relief valve. This study comprehensively considers the stability, rapidity, and immunity of relief valves and expands current investigations into the dynamic characteristics of relief valves from the perspective of classical control theory, thus revealing the importance of different parameters.
Current research on pilot-operated relief valve stability is primarily conducted from the perspective of system dynamics or stability criteria, and most of the existing conclusions focus on the spool shape, damping hole size, and pulsation frequency of the pump. However, the essential factors pertaining to the unstable vibration of relief valves remain ambiguous. In this study, the dynamic behavior of a pilot-operated relief valve is investigated using the frequency-domain method. The result suggests that the dynamic pressure feedback orifice is vital to the dynamic characteristics of the valve. A large orifice has a low flow resistance. In this case, the fluid in the main spring chamber flows freely, which is not conducive to the stability of the relief valve. However, a small orifice may create significant flow resistance, thus restricting fluid flow. In this case, the oil inside the main valve spring chamber is equivalent to a high-stiffness liquid spring. The main mass–spring vibration system has a natural frequency that differs significantly from the operating frequency of the relief valve, which is conducive to the stability of the relief valve. Good agreement is obtained between the theoretical analysis and experiments. The results indicate that designing a dynamic pressure feedback orifice of an appropriate size is beneficial to improving the stability of hydraulic pilot-operated relief valves. In addition, the dynamic pressure feedback orifice reduces the response speed of the relief valve. This study comprehensively considers the stability, rapidity, and immunity of relief valves and expands current investigations into the dynamic characteristics of relief valves from the perspective of classical control theory, thus revealing the importance of different parameters.
2023, 36: 87.
doi: 10.1186/s10033-023-00911-8
Abstract:
The meta-heuristic algorithm with local search is an excellent choice for the job-shop scheduling problem (JSP). However, due to the unique nature of the JSP, local search may generate infeasible neighbourhood solutions. In the existing literature, although some domain knowledge of the JSP can be used to avoid infeasible solutions, the constraint conditions in this domain knowledge are sufficient but not necessary. It may lose many feasible solutions and make the local search inadequate. By analysing the causes of infeasible neighbourhood solutions, this paper further explores the domain knowledge contained in the JSP and proposes the sufficient and necessary constraint conditions to find all feasible neighbourhood solutions, allowing the local search to be carried out thoroughly. With the proposed conditions, a new neighbourhood structure is designed in this paper. Then, a fast calculation method for all feasible neighbourhood solutions is provided, significantly reducing the calculation time compared with ordinary methods. A set of standard benchmark instances is used to evaluate the performance of the proposed neighbourhood structure and calculation method. The experimental results show that the calculation method is effective, and the new neighbourhood structure has more reliability and superiority than the other famous and influential neighbourhood structures, where 90% of the results are the best compared with three other well-known neighbourhood structures. Finally, the result from a tabu search algorithm with the new neighbourhood structure is compared with the current best results, demonstrating the superiority of the proposed neighbourhood structure.
The meta-heuristic algorithm with local search is an excellent choice for the job-shop scheduling problem (JSP). However, due to the unique nature of the JSP, local search may generate infeasible neighbourhood solutions. In the existing literature, although some domain knowledge of the JSP can be used to avoid infeasible solutions, the constraint conditions in this domain knowledge are sufficient but not necessary. It may lose many feasible solutions and make the local search inadequate. By analysing the causes of infeasible neighbourhood solutions, this paper further explores the domain knowledge contained in the JSP and proposes the sufficient and necessary constraint conditions to find all feasible neighbourhood solutions, allowing the local search to be carried out thoroughly. With the proposed conditions, a new neighbourhood structure is designed in this paper. Then, a fast calculation method for all feasible neighbourhood solutions is provided, significantly reducing the calculation time compared with ordinary methods. A set of standard benchmark instances is used to evaluate the performance of the proposed neighbourhood structure and calculation method. The experimental results show that the calculation method is effective, and the new neighbourhood structure has more reliability and superiority than the other famous and influential neighbourhood structures, where 90% of the results are the best compared with three other well-known neighbourhood structures. Finally, the result from a tabu search algorithm with the new neighbourhood structure is compared with the current best results, demonstrating the superiority of the proposed neighbourhood structure.
2023, 36: 88.
doi: 10.1186/s10033-023-00916-3
Abstract:
The full-field multiaxial strain measurement is highly desired for application of structural monitoring but still challenging, especially when the manufacturing and assembling for large-area sensing devices is quite difficult. Compared with the traditional procedure of gluing commercial strain gauges on the structure surfaces for strain monitoring, the recently developed Direct-Ink-Writing (DIW) technology provides a feasible way to directly print sensors on the structure. However, there are still crucial issues in the design and printing strategies to be probed and improved. Therefore, in this work, we propose an integrated strategy from layered circuit scheme to rapid manufacturing of strain rosette sensor array based on the DIW technology. Benefit from the innovative design with simplified circuit layout and the advantages of DIW for printing multilayer structures, here we achieve optimization design principle for strain rosette sensor array with scalable circuit layout, which enable a hierarchical printing strategy for multiaxial strain monitoring in large scale or multiple domains. The strategy is highly expected to adapt for the emerging requirement in various applications such as integrated soft electronics, nondestructive testing and small-batch medical devices.
The full-field multiaxial strain measurement is highly desired for application of structural monitoring but still challenging, especially when the manufacturing and assembling for large-area sensing devices is quite difficult. Compared with the traditional procedure of gluing commercial strain gauges on the structure surfaces for strain monitoring, the recently developed Direct-Ink-Writing (DIW) technology provides a feasible way to directly print sensors on the structure. However, there are still crucial issues in the design and printing strategies to be probed and improved. Therefore, in this work, we propose an integrated strategy from layered circuit scheme to rapid manufacturing of strain rosette sensor array based on the DIW technology. Benefit from the innovative design with simplified circuit layout and the advantages of DIW for printing multilayer structures, here we achieve optimization design principle for strain rosette sensor array with scalable circuit layout, which enable a hierarchical printing strategy for multiaxial strain monitoring in large scale or multiple domains. The strategy is highly expected to adapt for the emerging requirement in various applications such as integrated soft electronics, nondestructive testing and small-batch medical devices.
2023, 36: 92.
doi: 10.1186/s10033-023-00930-5
Abstract:
The current research on noncircular hobbing mainly focuses on the linkage model and motion realization. However, the intermittent cutting characteristics of hobbing would increase uncertainties in the manufacturing process. In this paper, a hobbing machining model with tool-shifting characteristics was proposed to solve the problems of cutting force fluctuation and inconsistency of tooth profile envelope accuracy at different positions of the pitch curve in noncircular gear hobbing. Based on the unit cutting force coefficient method, the undeformed chip volume generated by interrupted cutting was used to characterize the fluctuation trend of the hobbing force. The fluctuation characteristics of the cutting force generated by different hobbing models were compared and analyzed. Using the equivalent gear tooth and hob slotting numbers, an analysis model of the tooth profile envelope error of the noncircular gear was constructed. Subsequently, the tooth profile envelope errors at different positions of the pitch curve were compared and analyzed based on the constructed model. The transmission structure of the electronic gearbox was constructed based on the proposed hobbing model, and the hobbing experiment was conducted based on the self-developed noncircular gear CNC hobbing system. This paper proposes a hobbing method that can effectively suppress the fluctuation of the peak and whole circumference cutting force and reduce the maximum envelope error of the whole circumference gear teeth.
The current research on noncircular hobbing mainly focuses on the linkage model and motion realization. However, the intermittent cutting characteristics of hobbing would increase uncertainties in the manufacturing process. In this paper, a hobbing machining model with tool-shifting characteristics was proposed to solve the problems of cutting force fluctuation and inconsistency of tooth profile envelope accuracy at different positions of the pitch curve in noncircular gear hobbing. Based on the unit cutting force coefficient method, the undeformed chip volume generated by interrupted cutting was used to characterize the fluctuation trend of the hobbing force. The fluctuation characteristics of the cutting force generated by different hobbing models were compared and analyzed. Using the equivalent gear tooth and hob slotting numbers, an analysis model of the tooth profile envelope error of the noncircular gear was constructed. Subsequently, the tooth profile envelope errors at different positions of the pitch curve were compared and analyzed based on the constructed model. The transmission structure of the electronic gearbox was constructed based on the proposed hobbing model, and the hobbing experiment was conducted based on the self-developed noncircular gear CNC hobbing system. This paper proposes a hobbing method that can effectively suppress the fluctuation of the peak and whole circumference cutting force and reduce the maximum envelope error of the whole circumference gear teeth.
2023, 36: 93.
doi: 10.1186/s10033-023-00918-1
Abstract:
The footpad structure of a deep space exploration lander is a critical system that makes the initial contact with the ground, and thereby plays a crucial role in determining the stability and energy absorption characteristics during the impact process. The conventional footpad is typically designed with an aluminum honeycomb structure that dissipates energy through plastic deformation. Nevertheless, its effectiveness in providing cushioning and energy absorption becomes significantly compromised when the structure is crushed, rendering it unusable for reusable landers in the future. This study presents a methodology for designing and evaluating structural energy absorption systems incorporating recoverable strain constraints of shape memory alloys (SMA). The topological configuration of the energy absorbing structure is derived using an equivalent static load method (ESL), and three lightweight footpad designs featuring honeycomb-like Ni-Ti shape memory alloys structures and having variable stiffness skins are proposed. To verify the accuracy of the numerical modelling, a honeycomb-like structure subjected to compression load is modeled and then compared with experimental results. Moreover, the influence of the configurations and thickness distribution of the proposed structures on their energy absorption performance is comprehensively evaluated using finite element simulations. The results demonstrate that the proposed design approach effectively regulates the strain threshold to maintain the SMA within the constraint of maximum recoverable strain, resulting in a structural energy absorption capacity of 362 J/kg with a crushing force efficiency greater than 63%.
The footpad structure of a deep space exploration lander is a critical system that makes the initial contact with the ground, and thereby plays a crucial role in determining the stability and energy absorption characteristics during the impact process. The conventional footpad is typically designed with an aluminum honeycomb structure that dissipates energy through plastic deformation. Nevertheless, its effectiveness in providing cushioning and energy absorption becomes significantly compromised when the structure is crushed, rendering it unusable for reusable landers in the future. This study presents a methodology for designing and evaluating structural energy absorption systems incorporating recoverable strain constraints of shape memory alloys (SMA). The topological configuration of the energy absorbing structure is derived using an equivalent static load method (ESL), and three lightweight footpad designs featuring honeycomb-like Ni-Ti shape memory alloys structures and having variable stiffness skins are proposed. To verify the accuracy of the numerical modelling, a honeycomb-like structure subjected to compression load is modeled and then compared with experimental results. Moreover, the influence of the configurations and thickness distribution of the proposed structures on their energy absorption performance is comprehensively evaluated using finite element simulations. The results demonstrate that the proposed design approach effectively regulates the strain threshold to maintain the SMA within the constraint of maximum recoverable strain, resulting in a structural energy absorption capacity of 362 J/kg with a crushing force efficiency greater than 63%.
2023, 36: 97.
doi: 10.1186/s10033-023-00927-0
Abstract:
Cerium–lanthanum alloy is widely used in the green energy industry, and the nanoscale smooth surface of this material is in demand. Nanometric cutting is an effective approach to achieving the ultra-precision machining surface. Molecular dynamics (MD) simulation is usually used to reveal the atomic-scale details of the material removal mechanism in nanometric cutting. In this study, the effects of cutting speed and undeformed chip thickness (UCT) on cutting force and subsurface deformation of the cerium–lanthanum alloy during nanometric cutting are analyzed through MD simulation. The results illustrate that the dislocations, stacking faults, and phase transitions occur in the subsurface during cutting. The dislocations are mainly Shockley partial dislocation, and the increase of temperature and pressure during the cutting process leads to the phase transformation of γ-Ce (FCC) into β-Ce (HCP) and δ-Ce (BCC). β-Ce is mainly distributed in the stacking fault area, while δ-Ce is distributed in the boundary area between the dislocation atoms and γ-Ce atoms. The cutting speed and UCT affect the distribution of subsurface damage. A thicker deformed layer including dislocations, stacking faults and phase-transformation atoms on the machined surface is generated with the increase in the cutting speed and UCT. Simultaneously, the cutting speed and UCT significantly affect the cutting force, material removal rate, and generated subsurface state. The fluctuations in the cutting force are related to the generation and disappearance of dislocations. This research first studied the nanometric cutting mechanism of the cerium–lanthanum ally, providing a theoretical basis for the development of ultra-precision machining techniques of these materials.
Cerium–lanthanum alloy is widely used in the green energy industry, and the nanoscale smooth surface of this material is in demand. Nanometric cutting is an effective approach to achieving the ultra-precision machining surface. Molecular dynamics (MD) simulation is usually used to reveal the atomic-scale details of the material removal mechanism in nanometric cutting. In this study, the effects of cutting speed and undeformed chip thickness (UCT) on cutting force and subsurface deformation of the cerium–lanthanum alloy during nanometric cutting are analyzed through MD simulation. The results illustrate that the dislocations, stacking faults, and phase transitions occur in the subsurface during cutting. The dislocations are mainly Shockley partial dislocation, and the increase of temperature and pressure during the cutting process leads to the phase transformation of γ-Ce (FCC) into β-Ce (HCP) and δ-Ce (BCC). β-Ce is mainly distributed in the stacking fault area, while δ-Ce is distributed in the boundary area between the dislocation atoms and γ-Ce atoms. The cutting speed and UCT affect the distribution of subsurface damage. A thicker deformed layer including dislocations, stacking faults and phase-transformation atoms on the machined surface is generated with the increase in the cutting speed and UCT. Simultaneously, the cutting speed and UCT significantly affect the cutting force, material removal rate, and generated subsurface state. The fluctuations in the cutting force are related to the generation and disappearance of dislocations. This research first studied the nanometric cutting mechanism of the cerium–lanthanum ally, providing a theoretical basis for the development of ultra-precision machining techniques of these materials.
2023, 36: 98.
doi: 10.1186/s10033-023-00928-z
Abstract:
The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information. However, the separation performance depends largely on the construction of reference signals. To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed, the reference-based cubic blind deconvolution algorithm is proposed in this paper. The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration. The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved. By deriving the optimal step size of gradient iteration under the new contrast function, we propose an efficient adaptive step optimization method. Furthermore, the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation. Numerical simulation analysis is carried out to validate the availability and superiority of this method. Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness. The signals of control moment gyroscope and flywheel were extracted, respectively, and the contribution evaluation of vibration sources to the sensitive load area was realized. This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.
The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information. However, the separation performance depends largely on the construction of reference signals. To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed, the reference-based cubic blind deconvolution algorithm is proposed in this paper. The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration. The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved. By deriving the optimal step size of gradient iteration under the new contrast function, we propose an efficient adaptive step optimization method. Furthermore, the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation. Numerical simulation analysis is carried out to validate the availability and superiority of this method. Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness. The signals of control moment gyroscope and flywheel were extracted, respectively, and the contribution evaluation of vibration sources to the sensitive load area was realized. This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.
2023, 36: 102.
doi: 10.1186/s10033-023-00920-7
Abstract:
Variational mode decomposition (VMD) is a suitable tool for processing cavitation-induced vibration signals and is greatly affected by two parameters: the decomposed number K and penalty factor α under strong noise interference. To solve this issue, this study proposed self-tuning VMD (SVMD) for cavitation diagnostics in fluid machinery, with a special focus on low signal-to-noise ratio conditions. A two-stage progressive refinement of the coarsely located target penalty factor for SVMD was conducted to narrow down the search space for accelerated decomposition. A hybrid optimized sparrow search algorithm (HOSSA) was developed for optimal α fine-tuning in a refined space based on fault-type-guided objective functions. Based on the submodes obtained using exclusive penalty factors in each iteration, the cavitation-related characteristic frequencies (CCFs) were extracted for diagnostics. The power spectrum correlation coefficient between the SVMD reconstruction and original signals was employed as a stop criterion to determine whether to stop further decomposition. The proposed SVMD overcomes the blindness of setting the mode number K in advance and the drawback of sharing penalty factors for all submodes in fixed-parameter and parameter-optimized VMDs. Comparisons with other existing methods in simulation signal decomposition and in-lab experimental data demonstrated the advantages of the proposed method in accurately extracting CCFs with lower computational cost. SVMD especially enhances the denoising capability of the VMD-based method.
Variational mode decomposition (VMD) is a suitable tool for processing cavitation-induced vibration signals and is greatly affected by two parameters: the decomposed number K and penalty factor α under strong noise interference. To solve this issue, this study proposed self-tuning VMD (SVMD) for cavitation diagnostics in fluid machinery, with a special focus on low signal-to-noise ratio conditions. A two-stage progressive refinement of the coarsely located target penalty factor for SVMD was conducted to narrow down the search space for accelerated decomposition. A hybrid optimized sparrow search algorithm (HOSSA) was developed for optimal α fine-tuning in a refined space based on fault-type-guided objective functions. Based on the submodes obtained using exclusive penalty factors in each iteration, the cavitation-related characteristic frequencies (CCFs) were extracted for diagnostics. The power spectrum correlation coefficient between the SVMD reconstruction and original signals was employed as a stop criterion to determine whether to stop further decomposition. The proposed SVMD overcomes the blindness of setting the mode number K in advance and the drawback of sharing penalty factors for all submodes in fixed-parameter and parameter-optimized VMDs. Comparisons with other existing methods in simulation signal decomposition and in-lab experimental data demonstrated the advantages of the proposed method in accurately extracting CCFs with lower computational cost. SVMD especially enhances the denoising capability of the VMD-based method.
