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

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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Bibliographic Details
Main Authors: JU Chen, ZHANG Chao, FAN Hongwei, ZHANG Xuhui, YANG Yiqing, YAN Yang
Format: Article
Language:zho
Published: Editorial Department of Industry and Mine Automation 2020-08-01
Series:Gong-kuang zidonghua
Subjects:
coal mine rotating machinery
rolling bearing
fault diagnosis
wavelet packet decomposition
particle swarm optimization
bp neural network
Online Access:http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2019120022

Internet

http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2019120022

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