Failure mechanism-driven multi-adversarial domain transfer learning for rolling bearing fault diagnosis
The fault diagnosis of rolling bearings is crucial for ensuring the safe operation of mechanical equipment. However, existing data-driven methods often face performance bottlenecks in cross-condition diagnostic tasks due to a lack of understanding of physical failure mechanisms. Furthermore, they ar...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025022376 |
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