Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery.
Yadong XuXiaoan YanKe FengXin ShengBeibei SunZheng LiuPublished in: Reliab. Eng. Syst. Saf. (2022)
Keyphrases
- rotating machinery
- fault diagnosis
- denoising
- convolutional neural networks
- multiscale
- fault detection
- wavelet domain
- image processing
- image denoising
- natural images
- convolutional network
- expert systems
- neural network
- coarse to fine
- fuzzy logic
- bp neural network
- condition monitoring
- operating conditions
- gas turbine
- fault detection and diagnosis
- edge detection
- electronic equipment
- multiple faults
- failure diagnosis
- wavelet decomposition
- chemical process
- monitoring and fault diagnosis
- fault tree
- wavelet packet
- fault identification
- industrial systems
- power transformers
- power plant
- fault detection and isolation
- wavelet transform
- multi sensor information fusion