Rolling Bearing Fault Diagnosis Using Deep Transfer Learning Based on Joint Generalized Sliced Wasserstein Distance.
Na LeiJipeng CuiJicheng HanXian ChenYoufu TangPublished in: IEEE Access (2024)
Keyphrases
- transfer learning
- monitoring and fault diagnosis
- fault diagnosis
- knowledge transfer
- expert systems
- cross domain
- machine learning
- reinforcement learning
- labeled data
- active learning
- transfer knowledge
- fuzzy logic
- power transformers
- text categorization
- neural network
- fault detection
- text classification
- collaborative filtering
- multi sensor information fusion
- operating conditions
- domain adaptation
- fault detection and diagnosis
- gas turbine
- target domain
- multi task
- rotating machinery
- semi supervised learning
- text mining
- multiple faults
- semi supervised
- machine learning algorithms
- condition monitoring
- clustering algorithm
- electronic equipment
- support vector
- unlabeled data