Fault identification of rolling bearing based on multi hidden layers wavelet convolution extreme learning neural network

Fault identification of rolling bearing based on multi hidden layers wavelet convolution extreme learning neural network

The working environment of coal mine rotating machinery is harsh, and the actual collected rolling bearing vibration signals show the characteristics of obvious nonlinearity and non-stationarity. Therefore, it is difficult to extract bearing fault characteristics. The traditional rolling bearing fau...

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Bibliographic Details
Main Author: HUANG Chongqian
Format: Article
Language:zho
Published: Editorial Department of Industry and Mine Automation 2021-05-01
Series:Gong-kuang zidonghua
Subjects:
coal mine rotating machinery; rolling bearing fault identification; extreme learning machine; convolution neural network; auto-encoder
Online Access:http://www.gkzdh.cn/jn-abD.aspx?ArticleID=14518

Internet

http://www.gkzdh.cn/jn-abD.aspx?ArticleID=14518

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