Feature extraction for bearing fault diagnosis using composite multiscale entropy.
Shuen-De WuChiu-Wen WuShiou-Gwo LinChun-Chieh WangKung-Yen LeePublished in: AIM (2013)
Keyphrases
- fault diagnosis
- multiscale
- feature extraction
- monitoring and fault diagnosis
- wavelet transform
- image processing
- neural network
- fault detection
- expert systems
- fault detection and diagnosis
- operating conditions
- edge detection
- bp neural network
- power transformers
- condition monitoring
- fuzzy logic
- multiple faults
- electronic equipment
- gas turbine
- feature vectors
- support vector machine svm
- chemical process
- rotating machinery
- feature selection
- face recognition
- rbf neural network
- extracted features
- electrical power systems
- failure diagnosis
- feature space
- soft computing methods
- analog circuits
- frequency domain
- industrial systems
- texture features
- fault detection and isolation
- tennessee eastman
- multi sensor information fusion
- fault identification
- markov chain
- feature set
- decision making
- artificial intelligence
- data mining