A supervised sparsity-based wavelet feature for bearing fault diagnosis.
Cong WangMeng GanChang'an ZhuPublished in: J. Intell. Manuf. (2019)
Keyphrases
- fault diagnosis
- monitoring and fault diagnosis
- fault detection
- expert systems
- neural network
- bp neural network
- fuzzy logic
- electronic equipment
- power transformers
- wavelet transform
- gas turbine
- rotating machinery
- fault detection and diagnosis
- rbf neural network
- fault identification
- multiple faults
- vibration signal
- analog circuits
- machine learning
- industrial systems
- feature set
- partial discharge
- soft computing methods
- condition monitoring
- failure diagnosis
- feature selection
- denoising
- real time
- multi sensor information fusion
- power spectrum
- operating conditions
- wavelet coefficients
- multiscale
- data mining
- soft computing
- high frequency
- mathematical model
- electrical power systems
- tennessee eastman
- clustering algorithm