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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Strength
2023-12-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.06.001 |