A novel deep autoencoder and hyperparametric adaptive learning for imbalance intelligent fault diagnosis of rotating machinery.
Wanxiang LiZhiwu ShangMaosheng GaoShiqi QianBaoren ZhangJie ZhangPublished in: Eng. Appl. Artif. Intell. (2021)
Keyphrases
- adaptive learning
- rotating machinery
- fault diagnosis
- fault detection
- expert systems
- neural network
- industrial systems
- fault detection and diagnosis
- fuzzy logic
- learning objects
- operating conditions
- fuzzy classifier
- tennessee eastman
- multiple faults
- power transformers
- condition monitoring
- rbf neural network
- bp neural network
- chemical process
- learning environment
- gas turbine
- e learning
- electronic equipment
- concept maps
- analog circuits
- student model
- reinforcement learning
- learning activities
- intelligent systems
- multi sensor information fusion
- learning content
- real time
- monitoring and fault diagnosis