一种基于物理特征增强的跨域旋转机械故障诊断方法
By using a method based on physical feature enhancement and elastic weight solidification, the problems of data scarcity and small sample fit in cross-domain diagnosis of rotating machinery are solved, and efficient fault diagnosis results are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING
- Filing Date
- 2026-05-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for diagnosing rotating machinery faults suffer from problems such as scarce source domain data, insufficient fault samples, and catastrophic forgetting during the migration of small samples to the target domain, leading to a decrease in diagnostic accuracy.
A cross-domain fault diagnosis method based on physical feature enhancement is adopted. Enhanced samples that meet physical consistency constraints are generated by multi-dimensional physical feature extraction and difference-aware interpolation enhancement. The model is efficiently adapted by using elastic weight solidification fine-tuning technology.
It significantly improves the accuracy and generalization ability of fault diagnosis for rotating machinery, especially in cross-operating conditions and small sample scenarios. It effectively preserves source domain knowledge, avoids model overfitting and forgetting, and achieves efficient fault diagnosis.
Smart Images
Figure CN122133041B_ABST