Rolling bearing fault diagnosis based on wavelet packet decomposition and PSO-BPN

In view of problems in existing rolling bearing fault diagnosis methods for coal mine rotating machinery, such as incomplete signal feature extraction, low fault diagnosis accuracy and low efficiency, a rolling bearing fault diagnosis method based on wavelet packet decomposition and particle swarm o...

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Auteurs principaux:	JU Chen, ZHANG Chao, FAN Hongwei, ZHANG Xuhui, YANG Yiqing, YAN Yang
Format:	Artigo
Langue:	Chinês
Publié:	Editorial Department of Industry and Mine Automation 2020-08-01
Collection:	Gong-kuang zidonghua
Sujets:	coal mine rotating machinery rolling bearing fault diagnosis wavelet packet decomposition particle swarm optimization bp neural network
Accès en ligne:	http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2019120022
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