Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine

Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine

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ObjectiveIn response to challenges such as large sampling data, extended diagnosis time, and subjective fault feature selection in traditional bearing fault diagnosis, a CS-DMKELM intelligent diagnosis model for rolling bearings is proposed based on compressed sensing(CS) and deep multi-kernel extre...

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Bibliographic Details
Main Authors: FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2024-01-01
Series:Jixie qiangdu
Subjects:
Compressed sensing
Bearing
Kernel function
Extreme learning machine
Fault diagnosis
Online Access:http://www.jxqd.net.cn/thesisDetails?columnId=78737352&Fpath=home&index=0
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