A hybrid feature selection scheme for unsupervised learning and its application in bearing fault diagnosis.
Yang YangYinxia LiaoGuang MengJay LeePublished in: Expert Syst. Appl. (2011)
Keyphrases
- selection scheme
- fault diagnosis
- unsupervised learning
- monitoring and fault diagnosis
- selection algorithm
- neural network
- fault detection
- expert systems
- supervised learning
- bp neural network
- power transformers
- chemical process
- fuzzy logic
- operating conditions
- rbf neural network
- fault detection and diagnosis
- rotating machinery
- condition monitoring
- multiple faults
- analog circuits
- electronic equipment
- gas turbine
- machine learning
- regression model
- dimensionality reduction
- feature vectors
- learning algorithm
- cluster analysis
- back propagation
- semi supervised
- pattern recognition
- knowledge base
- multi sensor information fusion