A class-level matching unsupervised transfer learning network for rolling bearing fault diagnosis under various working conditions.
Chunran HuoQuansheng JiangYehu ShenXiaoshan LinQixin ZhuQingkui ZhangPublished in: Appl. Soft Comput. (2023)
Keyphrases
- monitoring and fault diagnosis
- fault diagnosis
- transfer learning
- operating conditions
- knowledge transfer
- neural network
- fault detection
- manifold alignment
- expert systems
- labeled data
- cross domain
- fuzzy logic
- bp neural network
- machine learning
- chemical process
- reinforcement learning
- fault detection and diagnosis
- multi task
- active learning
- semi supervised learning
- semi supervised
- power transformers
- transfer knowledge
- network structure
- analog circuits
- condition monitoring
- class labels
- machine learning algorithms
- unsupervised learning
- text classification
- text categorization
- gas turbine
- multiple faults
- collaborative filtering
- multi sensor information fusion