An Adaptive Spectrum Segmentation Method to Optimize Empirical Wavelet Transform for Rolling Bearings Fault Diagnosis.
Yonggang XuKun ZhangChaoyong MaZhipeng ShengHongchen ShenPublished in: IEEE Access (2019)
Keyphrases
- segmentation method
- fault diagnosis
- vibration signal
- monitoring and fault diagnosis
- wavelet transform
- condition monitoring
- fault detection
- multiresolution
- operating conditions
- multiscale
- region growing
- active contours
- neural network
- image segmentation
- power spectrum
- bp neural network
- subband
- wavelet analysis
- expert systems
- image compression
- electronic equipment
- multiple faults
- segmentation algorithm
- automated segmentation
- energy function
- fault detection and diagnosis
- power transformers
- denoising
- wavelet coefficients
- wavelet filters
- fuzzy logic
- autoregressive
- analog circuits
- rotating machinery
- morphological filters
- real time
- gas turbine
- chemical process
- mathematical model
- feature extraction
- extracted features
- information fusion
- steady state
- multi sensor information fusion