A Deep Transfer Nonnegativity-Constraint Sparse Autoencoder for Rolling Bearing Fault Diagnosis With Few Labeled Data.
Li XingqiuHongkai JiangKe ZhaoRuixin WangPublished in: IEEE Access (2019)
Keyphrases
- monitoring and fault diagnosis
- labeled data
- fault diagnosis
- transfer learning
- unlabeled data
- semi supervised
- semi supervised learning
- active learning
- supervised learning
- training data
- text classification
- pairwise constraints
- knowledge transfer
- expert systems
- domain adaptation
- class labels
- labeled training data
- neural network
- learning tasks
- data points
- fault detection
- labeled and unlabeled data
- fuzzy logic
- condition monitoring
- operating conditions
- cross domain
- prior knowledge
- sparse representation
- training examples
- multiple faults
- chemical process
- multi sensor information fusion
- rbf neural network
- co training
- nonnegative matrix factorization
- target domain
- transferring knowledge
- reinforcement learning
- machine learning