A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures.
Shoucong XiongHongdi ZhouShuai HeLeilei ZhangQi XiaJianping XuanTielin ShiPublished in: Sensors (2020)
Keyphrases
- end to end
- fault diagnosis
- wavelet packet transform
- analog circuits
- monitoring and fault diagnosis
- network architecture
- neural network
- condition monitoring
- fault detection
- wavelet packet
- vibration signal
- operating conditions
- shift invariant
- expert systems
- multi sensor information fusion
- fuzzy logic
- wavelet coefficients
- digital circuits
- texture features
- denoising
- wavelet transform
- decision making
- feature extraction
- sparse coding
- neural network model
- watermarking algorithm
- high frequency
- frequency band
- sample set
- training data