Deep Convolutional and LSTM Recurrent Neural Networks for Rolling Bearing Fault Diagnosis Under Strong Noises and Variable Loads.
Meiying QiaoShuhao YanXiaxia TangChengkuan XuPublished in: IEEE Access (2020)
Keyphrases
- recurrent neural networks
- monitoring and fault diagnosis
- fault diagnosis
- neural network
- long short term memory
- deep learning
- expert systems
- fault detection
- reservoir computing
- artificial neural networks
- recurrent networks
- electronic equipment
- fuzzy logic
- feed forward
- bp neural network
- feedforward neural networks
- hidden layer
- condition monitoring
- rbf neural network
- fault detection and diagnosis
- echo state networks
- chemical process
- nonlinear dynamic systems
- rotating machinery
- industrial systems
- operating conditions
- probabilistic neural networks
- gas turbine
- multiple faults
- fault identification
- power plant
- power transformers
- decision making
- genetic algorithm