Rolling Bearing Fault Diagnosis Based on Time-Frequency Feature Extraction and IBA-SVM.
Mei ZhangJun YinWanli ChenPublished in: IEEE Access (2022)
Keyphrases
- monitoring and fault diagnosis
- fault diagnosis
- support vector machine svm
- feature extraction
- feature vectors
- wavelet transform
- support vector
- feature selection
- frequency domain
- support vector machine
- neural network
- vibration signal
- fault detection
- expert systems
- rbf neural network
- chemical process
- extracted features
- condition monitoring
- bp neural network
- gas turbine
- feature space
- operating conditions
- face recognition
- fault detection and isolation
- kernel function
- electrical power systems
- multi sensor information fusion
- industrial systems
- power transformers
- fault identification
- electronic equipment
- support vector regression
- knn
- fuzzy logic
- radial basis function
- image processing
- failure diagnosis
- analog circuits
- knowledge base
- fault detection and diagnosis
- decision making
- subband
- feature set
- training data
- rotating machinery
- machine learning
- real time
- training set