Bearing compound fault diagnosis method with adaptive dual-damped wavelet dictionary

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Journal of Vibration and Shock ›› 2025, Vol. 44 ›› Issue (7) : 239-246.

FAULT DIAGNOSIS ANALYSIS

Bearing compound fault diagnosis method with adaptive dual-damped wavelet dictionary

HU Junfeng1, ZHAO Lijuan2, YAN Xuezhu2, ZHANG Long*2

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Abstract

Aiming at the problem of extracting the effective features of each signal component for bearing compound fault under heavy background noise, a novel compound fault diagnosis method based on maximum correlated kurtosis deconvolution（MCKD） and sparse representation is proposed. Firstly, the MCKD algorithm is used to separate the compound faults and enhance the fault impulse responses. Next, a priori knowledge analysis of the sparse representation dictionary design is carried out to construct a double-damped asymmetric wavelet parameter dictionary that better matches the real fault impulse response, which is combined with Orthogonal Matching Pursuit (OMP) algorithm to sparsely reconstruct each fault feature. Finally, the reconstructed components are analyzed by envelope spectrum to extract fault characteristic frequencies. Considering that parameter selection in the MCKD algorithm and asymmetric wavelets determines the final feature extraction effect, the Whale Optimization Algorithm (WOA) is used to achieve automatic and optimal parameter selection. The analysis results of the simulated signals and the test-bed signals show that the proposed method can effectively extract all kinds of fault components in bearing compound faults, and has certain superiority over the commonly used single-damped Laplace wavelet dictionary.

Key words

compound fault / maximum correlated kurtosis deconvolution（MCKD） algorithm / double-damped asymmetric wavelet / sparse representation / feature extraction.

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HU Junfeng1, ZHAO Lijuan2, YAN Xuezhu2, ZHANG Long2. Bearing compound fault diagnosis method with adaptive dual-damped wavelet dictionary[J]. Journal of Vibration and Shock, 2025, 44(7): 239-246

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