End-to-end CNN + LSTM deep learning approach for bearing fault diagnosis.
Amin KhorramMohammad KhalooeiMansoor RezghiPublished in: Appl. Intell. (2021)
Keyphrases
- end to end
- deep learning
- fault diagnosis
- monitoring and fault diagnosis
- neural network
- unsupervised learning
- recurrent neural networks
- expert systems
- machine learning
- fault detection
- fuzzy logic
- operating conditions
- electronic equipment
- chemical process
- fault detection and diagnosis
- weakly supervised
- gas turbine
- congestion control
- condition monitoring
- analog circuits
- power transformers
- multi sensor information fusion
- mental models
- multiple faults
- computer vision
- learning strategies
- object detection
- knowledge base