Rolling Bearing Fault Diagnosis Using Modified LFDA and EMD With Sensitive Feature Selection.
Xiao YuFei DongEnjie DingShoupeng WuChunyang FanPublished in: IEEE Access (2018)
Keyphrases
- monitoring and fault diagnosis
- fault diagnosis
- feature selection
- neural network
- fault detection
- expert systems
- rbf neural network
- fault detection and diagnosis
- distance measure
- rotating machinery
- fuzzy logic
- electronic equipment
- feature extraction
- power transformers
- bp neural network
- support vector machine
- feature space
- chemical process
- industrial systems
- gas turbine
- analog circuits
- failure diagnosis
- operating conditions
- probabilistic neural networks
- power plant
- high dimensional
- support vector
- machine learning
- condition monitoring
- real time
- mathematical model
- multiple faults
- fault identification
- electrical power systems
- steam turbine
- tennessee eastman
- multi sensor information fusion