A novel sub-label learning mechanism for enhanced cross-domain fault diagnosis of rotating machinery.
Minqiang DengAidong DengYaowei ShiYang LiuMeng XuPublished in: Reliab. Eng. Syst. Saf. (2022)
Keyphrases
- rotating machinery
- learning mechanism
- cross domain
- fault diagnosis
- fault detection
- neural network
- transfer learning
- expert systems
- knowledge transfer
- rbf neural network
- fault detection and diagnosis
- learning process
- operating conditions
- electronic equipment
- learning algorithm
- multiple faults
- analog circuits
- bp neural network
- multi label
- text categorization
- monitoring and fault diagnosis
- power transformers
- fuzzy logic
- case study
- gas turbine
- learning rules
- machine learning
- chemical process
- multi sensor information fusion
- target domain
- real time
- class labels
- artificial intelligence
- power plant
- decision making
- training data
- learning environment
- e government