A semi-supervised transferable LSTM with feature evaluation for fault diagnosis of rotating machinery.
Zhi TangLin BoXiaofeng LiuDaiping WeiPublished in: Appl. Intell. (2022)
Keyphrases
- rotating machinery
- fault diagnosis
- fault detection
- semi supervised
- neural network
- expert systems
- fuzzy logic
- multi sensor information fusion
- fault detection and diagnosis
- industrial systems
- operating conditions
- bp neural network
- monitoring and fault diagnosis
- analog circuits
- power transformers
- gas turbine
- recurrent neural networks
- rbf neural network
- semi supervised learning
- unlabeled data
- fault identification
- multiple faults
- condition monitoring
- feature vectors
- failure diagnosis
- soft computing methods
- artificial intelligence
- chemical process
- evaluation method
- labeled data
- feature set
- power plant
- evolutionary computation
- artificial neural networks