Fault diagnosis of power equipment based on variational autoencoder and semi-supervised learning.
Bo YeFeng LiLinghao ZhangZhengwei ChangBin WangXiaoyu ZhangSayina BodanbaiPublished in: Concurr. Comput. Pract. Exp. (2024)
Keyphrases
- semi supervised learning
- fault diagnosis
- semi supervised
- unlabeled data
- labeled data
- expert systems
- dirichlet process mixture models
- neural network
- supervised learning
- fault detection
- unsupervised learning
- semi supervised classification
- machine learning
- bp neural network
- chemical process
- rbf neural network
- co training
- manifold regularization
- multiple faults
- monitoring and fault diagnosis
- operating conditions
- label propagation
- power transformers
- fuzzy logic
- active learning
- wind turbine
- text classification
- training data
- image segmentation
- multi sensor information fusion
- analog circuits
- transfer learning
- data fusion
- graph based semi supervised learning
- learning tasks
- control system
- k means
- artificial intelligence
- real world