Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples.
Daoguang YangHamid Reza KarimiKangkang SunPublished in: Neural Networks (2021)
Keyphrases
- rotating machinery
- fault diagnosis
- fault detection
- industrial systems
- expert systems
- deep learning
- fault detection and diagnosis
- gas turbine
- kernel function
- neural network
- fuzzy logic
- rbf neural network
- operating conditions
- power transformers
- fault identification
- failure diagnosis
- monitoring and fault diagnosis
- analog circuits
- multiple faults
- support vector
- intelligent systems
- condition monitoring
- bp neural network
- bit rate
- knowledge based expert systems
- training set
- soft computing methods
- electronic equipment
- multi sensor information fusion
- training samples
- artificial neural networks
- electrical power systems
- steam turbine
- tennessee eastman