《机电工程》杂志社科技期刊核心期刊论文投稿机电一体化机械、仪表电工自动化、计算机浙江大学主办

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Bearing real-time fault diagnosis based on SQSWOMP algorithm

Published:2022-12-20 author:QIAN Zi-jun, WU Bo, YU Jian-feng, et al. Browse: 490 Check PDF documents

Bearing real-time fault diagnosis based on SQSWOMP algorithm

QIAN Zi-jun1,2, WU Bo1, YU Jian-feng1, WANG Wen-rui1,

WANG Zhen-ming1, YUAN Xiao-bing3

(1.Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 200120, China; 2.University

of Chinese Academy of Sciences, Beijing 100089, China; 3.Shanghai Institute of Microsystem and Information

Technology, Chinese Academy of Sciences, Shanghai 200233, China)

Abstract: Aiming at the problems in the bearing fault diagnosis method, such as low efficiency of data storage, transmission and processing, and large number of model parameters leading to waste of resources and low diagnostic accuracy. Based on the improved stagewise weakly orthogonal matching pursuit (SWOMP) algorithm, in view of the problem of low reconstruction accuracy in the SWOMP algorithm, a sigmoid function and a secondary selection process for the atomic support set were introduced into the SWOMP algorithm. A realtime fault diagnosis method for bearings based on Sshaped quadratic stagewise weak orthogonal matching pursuit (SQSWOMP) algorithm was proposed.Firstly, the initial dictionary was obtained by partitioning the bearing history data into matrices with sliding shift windows, while the overcomplete dictionary was established with the improved KSVD algorithm.Then, SQSWOMP algorithm was combined with the trained overcomplete dictionary to reconstruct the realtime vibration signals.Finally, the reconstructed signals were sparsely decomposed by using the feature that the dictionary could effectively decompose the specific state signals, but not the other state signals. The results indicate that the reconstruction accuracy and efficiency of SQSWOMP algorithm are better than other matching and tracking algorithms, which can solve the problem of low reconstruction accuracy of SWOMP algorithm. The accuracy of normal, inner ring, outer ring, and rolling body fault diagnosis are improved by 2.17%, 23.46%, 17.30%, and 18.38% without consuming a lot of storage and transmission resources. The accuracy is better than other methods, which can facilitate real-time fault diagnosis.

Key words: stagewise weak orthogonal matching pursuit (SWOMP); S-shaped quadratic stagewise weak orthogonal matching pursuit (SQSWOMP); compressed sensingtheory; signal reconstruction; sparse representation; improved greedy algorithm

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