Semi-supervised fault diagnosis of machinery using LPS-DGAT under speed fluctuation and extremely low labeled rates.
Shen YanHaidong ShaoYiming XiaoJian ZhouYuandong XuJiafu WanPublished in: Adv. Eng. Informatics (2022)
Keyphrases
- fault diagnosis
- semi supervised
- supervised learning
- expert systems
- fault detection
- neural network
- gas turbine
- fault detection and diagnosis
- bp neural network
- multiple faults
- labeled data
- wind turbine
- semi supervised learning
- fuzzy logic
- rotating machinery
- training data
- operating conditions
- monitoring and fault diagnosis
- condition monitoring
- power transformers
- electrical power systems
- chemical process
- unlabeled data
- analog circuits
- steam turbine
- industrial systems
- electronic equipment
- rbf neural network
- fault detection and isolation
- fault identification
- real time
- fault tree
- pairwise
- soft computing methods
- artificial intelligence
- failure diagnosis
- active learning
- control system