FAULT DIAGNOSIS FOR GEARBOXGEAR BASED ON CONTINUOUS WAVELET TRANSFORM

Abstract

Abstract: Continuous wavelet transform (CWT) has a finer scale resolution than dyadic discrete wavelet transform and wavelet packet transform. The concept of time averaged wavelet spectrum (TAWS) based on Morlet CWT is proposed and two fault diagnosis methods named spectra comparison (SC) and feature energy (FE) based on TAWS are established. The results of the application to gearbox gear fault diagnosis show that TAWS can effectively extract gear fault information, and that SC and FE can accurately detect the gear fault level, and that the feature energy of the TAWS is comic proportional to the gear fault level.

Key words: Continuous wavelet transform, Fault advancement, Fault diagnosis, Gearbox gear, Time averaged wavelet spectrum

CLC Number:

TH165.3

Zheng Haibo;Li Zhiyuan;Chen Xinzhao. FAULT DIAGNOSIS FOR GEARBOXGEAR BASED ON CONTINUOUS WAVELET TRANSFORM[J]. , 2002, 38(3): 69-73.

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FAULT DIAGNOSIS FOR GEARBOXGEAR BASED ON CONTINUOUS WAVELET TRANSFORM

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