Episodic Training and Feature Orthogonality-Driven Domain Generalization for Rotating Machinery Fault Diagnosis Under Unseen Working Conditions
In recent years, domain generalization-based fault diagnosis (DGFD) methods have shown significant potential in rotating machinery fault diagnosis in unseen target domains. However, these methods focus on learning domain-invariant representations via feature distribution adaptation. The generalizati...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/13/7/563 |
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