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  HomeContents of Chinese Journal of Mechanical Engineering (English Edition),2006 No.2AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARACTERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICRO- ELECTROCHEMICAL MACHINING

TANG Xinglun

Department of Precision

Instrument & Mechanics,

Tsinghua University,

Beijing 100084, China

 

ZHANG Zhijing

School of Mechanical & Vehicle

 Engineering,

Beijing Institute of Technology,

Beijing 100084, China

 

 ZHOU Zhaoying

Department of Precision

Instrument & Mechanics,

Tsinghua University,

Beijing 100084, China

 

YANG Xiaodong

Equipment & Energy Department,

Guizhou Branch of Aluminum Co., Ltd., Guiyang 550014, China

 

 

AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARACTERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICRO- ELECTROCHEMICAL MACHINING*

 

Abstract: The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining (HGPECM) is mainly discussed. The auto-regressive(AR) model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green’s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum(CPS), to the current signals related to the different inter-electrode gap size in the range of 0~5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.

Key words: Electrochemical machining  Inter-electrode gap  Autoregressive(AR) model  Power spectrum

 


* This project is supported by the 10th Five-year Plan Pre-research Project Foundation of China Weapon Industry Company, China (No.42001080701). Received July 19, 2005; received in revised form January 24, 2006; accepted March 6, 2006

 

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