KurVMDPgram: Signal Decomposition Algorithm for Fault Diagnosis of Rotating Machinery

doi:10.3901/JME.2025.04.011

Abstract

Abstract: Variational mode decomposition(VMD) is a signal decomposition method which is widely used in the field of rotating machinery fault diagnosis. However, several influencing parameters of VMD, especially the mode number and penalty factor, need to be determined in advance, which makes the parameter optimizations of VMD become a research hotspot. A new signal decomposition method, namely variational mode packet decomposition(VMD Packet, VMPD), is constructed by combining the binary decomposition mode of wavelet packet transform(WPT) and the Wiener filtering characteristics of VMD. Then, a tiled VMDP is constructed, and the VMDPgram method is proposed. The VMDPgram is proposed to use VMD to realize the decomposition of the WPT mode of the signal. In VMDPgram, the original signal is decomposed into a certain level of sub-components(SCs), where each VMD generates two SCs, thereby simplifying the multi-parameter problem into a single-parameter problem. The penalty factor of each VMD in the VMDPgram is optimized by using the kurtosis index, and then the KurVMDPgram method is proposed. Then, the strategy of cumulative kurtosis index is proposed to select the optimal SC of KurVMDPgram, which can solve the situation that the resonant frequency band is decomposed into different SCs without pre-judging them. Finally, the validity and superiority of KurVMDPgram are proved by simulation case and actual bearing fault cases.

Key words: variational mode decomposition, wavelet packet transform, VMDPgram, KurVMDPgram, cumulative kurtosis index, fault diagnosis

CLC Number:

TH165
TH17

LI Hua, WANG Tianyang, ZHANG Feibin, CHU Fulei. KurVMDPgram: Signal Decomposition Algorithm for Fault Diagnosis of Rotating Machinery[J]. Journal of Mechanical Engineering, 2025, 61(4): 11-23.

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