Fault diagnosis of planetary gearbox based on parameter optimized VMD and multi-domain manifold learning

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Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (1) : 110-118.

WANG Zhenya1, YAO Ligang1, QI Xiaoli2, ZHANG Jun1, ZHENG Jinde2

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Abstract

Aiming at the problem of features extraction of planetary gearbox being difficult, a fault diagnosis method based on parameter optimized variational mode decomposition (VMD) and multi-domain manifold learning was proposed. Firstly, the salp swarm optimization variational mode decomposition (SSO-VMD) was utilized to decompose and reconstruct signals to reduce noise interference. Then, fault features were extracted from multi-domain, and the improved supervised self-organizing incremental learning neural network boundary punctuation isometric mapping (ISSL-Isomap) algorithm was used to reduce dimension, and acquire low-dimensional fault features. Finally, the artificial bee colony support vector machine (ABC-SVM) multi-fault classifier was used to do diagnosis and identification. The SSO-VMD was compared with the empirical mode decomposition (EMD), and the superiority of SSO-VMD was verified with simulation signal analysis results. The proposed fault diagnosis method was applied in planetary gearbox fault diagnosis test analysis. Results showed that the multi-domain feature extraction is better than the feature extraction in single-domain including time domain, frequency one and scale one; the dimension reduction effect of ISSL-Isomap is better than those of Isomap, t-distributed stochastic neighborhood embedding, linear discriminant analysis, weighted Isomap and supervised Isomap; the fault recognition rate of the proposed method reaches 100%, and it can effectively recognize various types working conditions of planetary gearbox.

Key words

variational mode decomposition (VMD) / isometric mapping (Isomap) / manifold learning / support vector machine / planetary gearbox / fault diagnosis

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WANG Zhenya1, YAO Ligang1, QI Xiaoli2, ZHANG Jun1, ZHENG Jinde2. Fault diagnosis of planetary gearbox based on parameter optimized VMD and multi-domain manifold learning[J]. Journal of Vibration and Shock, 2021, 40(1): 110-118

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