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ZHANG Xinming
HE Yongyong
HAO Rujiang
CHU Fulei
State Key Laboratory of Tribology,
Tsinghua University,
Beijng 100084, China
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PARAMETERS OPTIMIZATION
OF CONTINUOUS WAVELET
TRANSFORM AND ITS APPLICATION IN ACOUSTIC EMISSION SIGNAL
ANALYSIS OF ROLLING BEARING*
Abstract:
Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform (CWT) has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission (AE) signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.
Key words:
Rolling bearing Fault diagnosis Acoustic emission (AE)
Continuous wavelet transform (CWT) Genetic algorithm
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