FAULT DIAGNOSIS OF WIND TURBINE BEARING BASED ON SENET-RESNEXT-LSTM

FAULT DIAGNOSIS OF WIND TURBINE BEARING BASED ON SENET-RESNEXT-LSTM

A large number of complex features need to be extracted for the fault diagnosis of wind turbine rolling bearings. A parallel bearing fault diagnosis model based on attention mechanism, ResNext network and long short-term memory (LSTM) network was proposed. Firstly, the collected one-dimensional vibr...

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Bibliographic Details
Main Authors: DU HaoFei, ZHANG Chao, LI JianJun
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2023-12-01
Series:Jixie qiangdu
Subjects:
Fault diagnosis
Attention mechanism
ResNext
LSTM
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.06.001
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