LDA-based deep transfer learning for fault diagnosis in industrial chemical processes.
Yalin WangDongzhe WuXiaofeng YuanPublished in: Comput. Chem. Eng. (2020)
Keyphrases
- transfer learning
- fault diagnosis
- industrial systems
- gas turbine
- chemical process
- fault detection
- fault diagnostic
- industrial processes
- knowledge transfer
- neural network
- labeled data
- expert systems
- industrial applications
- fuzzy logic
- fault detection and diagnosis
- active learning
- reinforcement learning
- machine learning
- operating conditions
- rotating machinery
- semi supervised learning
- condition monitoring
- monitoring and fault diagnosis
- electronic equipment
- cross domain
- power transformers
- target domain
- machine learning algorithms
- text classification
- collaborative filtering
- text categorization
- multiple faults
- text mining
- data sets
- training data
- transfer knowledge
- analog circuits
- semi supervised
- decision trees
- artificial intelligence
- genetic algorithm
- domain adaptation
- test set
- fuzzy sets
- computational intelligence
- multi sensor information fusion