A physics-informed deep learning approach for bearing fault detection.
Sheng ShenHao LuMohammadkazem SadoughiChao HuVenkat NemaniAdam ThelenKeith WebsterMatthew J. DarrJeff SidonShawn KennyPublished in: Eng. Appl. Artif. Intell. (2021)
Keyphrases
- deep learning
- fault detection
- fault diagnosis
- fault identification
- tennessee eastman
- unsupervised learning
- condition monitoring
- industrial processes
- machine learning
- robust fault detection
- weakly supervised
- unsupervised feature learning
- mental models
- fuel cell
- failure detection
- artificial intelligence
- image segmentation
- power plant
- higher order
- genetic algorithm
- neural network