Fault Feature Analysis and Diagnosis Method of Rolling Bearing based on Empirical Mode Decomposition and Deep Belief Network

Fault Feature Analysis and Diagnosis Method of Rolling Bearing based on Empirical Mode Decomposition and Deep Belief Network

In order to realize the intelligent diagnosis of rolling bearing failure,a fault diagnosis model of vibration signal based on empirical mode decomposition（ EMD） and deep belief network（ DBN） is proposed.Firstly,the vibration signal is processed by empirical mode decomposition,and the statistical par...

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Bibliographic Details
Main Authors: Yu Xiao, Fan Chunyang, Dong Fei, Ding Enjie, Wu Shoupeng, Wang Xin
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2018-01-01
Series:Jixie chuandong
Subjects:
Empirical modal decomposition
Extreme learning machine
Deep belief network
Rolling bearing
Fault diagnosis
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.06.033

Internet

http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.06.033

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