Prediction of Bearing Remaining Service Life Based on CNN-LSTM

Prediction of Bearing Remaining Service Life Based on CNN-LSTM

Aiming at the waste of resources caused by the bearing reaching the service time and still meeting the service conditions, a bearing remaining service life prediction method based on CNN-LSTM is proposed. Firstly, a high-speed railway traction motor bearing which has completed service but is still h...

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Bibliographic Details
Main Authors: Cai Weiwei, Xu Yanwei, Xie Tancheng
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2022-01-01
Series:Jixie chuandong
Subjects:
Rolling bearing;CNN-LSTM;Remaining service life prediction;Long and short term memory network
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.10.003

Internet

http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.10.003

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