Fault diagnosis of unknown device based on dynamic model and domain generalization
Author:
Affiliation:
1. Xinjiang University,College of Electrical Engineering,Urumqi,China
2. Wind Power Equipment Co., Ltd,Beijing Goldwind Science and Technology Innovation,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10598401/10598402/10598467.pdf?arnumber=10598467
Reference14 articles.
1. A motor bearing fault voiceprint recognition method based on Mel-CNN model
2. A Multi-Indicator Fusion-Based Approach for Fault Feature Selection and Classification of Rolling Bearings
3. A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems
4. Multiscale Fusion Attention Convolutional Neural Network for Fault Diagnosis of Aero-Engine Rolling Bearing
5. Enhancing Bearing Fault Diagnosis Using Transfer Learning and Random Forest Classification: A Comparative Study on Variable Working Conditions
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