Fault Diagnosis of Rolling Bearing Based on Adaptive Block Forward and Backward Stagewise Orthogonal Matching Pursuit Algorithm

doi:10.3901/JME.2020.09.091

Abstract

Abstract: In the process of block compression sensing of rolling bearing fault signal, the reconstruction accuracy of the signal is low due to the large difference in sparsity between blocks and the unreasonable components of reconstruction support set, which affects the overall reconstruction effect of the signal. In order to improve the signal reconstruction results, adaptive block forward and backward stagewise orthogonal matching pursuit (Adaptive Block-FBStOMP) algorithm based on adaptive block method is proposed. Firstly, the adaptive block length of the rolling bearing fault signal is determined according to the short-time autocorrelation algorithm, and the signal is divided into signal blocks according to the adaptive block length to equalize the sparsity of each block. Secondly, the K-singular value decomposition (K-SVD) algorithm is used to train the sparse dictionary of each block to obtain better sparse effect. Finally, the FBStOMP reconstruction algorithm is proposed. The atom backtracking and quadratic screening processes are added in the reconstruction process to improve the possibility that all the effective support set atoms can be selected into the support set. The experimental analysis of the simulation signal and the bearing fault signal shows that, compared with the traditional compressed sensing reconstruction algorithm, the proposing algorithm can effectively improve the reconstruction accuracy of the bearing fault signal.

Key words: compression sensing, adaptive block, reconstruction algorithm, sparse dictionary

CLC Number:

TG156

MENG Zong, SHI Ying, PAN Zuozhou, CHEN Zijun. Fault Diagnosis of Rolling Bearing Based on Adaptive Block Forward and Backward Stagewise Orthogonal Matching Pursuit Algorithm[J]. Journal of Mechanical Engineering, 2020, 56(9): 91-101.

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