Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification.
Chen LuZhenya WangWei-Li QinJian MaPublished in: Signal Process. (2017)
Keyphrases
- fault diagnosis
- denoising
- fault detection
- expert systems
- neural network
- bp neural network
- rotating machinery
- electronic equipment
- multiple faults
- chemical process
- analog circuits
- fault detection and diagnosis
- power transformers
- gas turbine
- rbf neural network
- fuzzy logic
- monitoring and fault diagnosis
- condition monitoring
- power plant
- operating conditions
- industrial systems
- computational intelligence
- fault identification
- electrical power systems
- failure diagnosis
- intelligent systems
- state space
- control system
- fault tree
- machine learning