Deep transfer learning for rolling bearing fault diagnosis under variable operating conditions
Rolling bearings are the vital components of rotary machines. The collected data of rolling bearing have strong noise interference, massive unlabeled samples, and different fault features. Thus, a deep transfer learning method is proposed for rolling bearings fault diagnosis under variable operating...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2019-12-01
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| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1177/1687814019897212 |