CLFormer: A Lightweight Transformer Based on Convolutional Embedding and Linear Self-Attention With Strong Robustness for Bearing Fault Diagnosis Under Limited Sample Conditions.
Hairui FangJin DengYaoxu BaiBo FengSheng LiSiyu ShaoDongsheng ChenPublished in: IEEE Trans. Instrum. Meas. (2022)
Keyphrases
- fault diagnosis
- lightweight
- strong robustness
- bp algorithm
- monitoring and fault diagnosis
- operating conditions
- power transformers
- bp neural network
- fault detection
- neural network
- expert systems
- fuzzy logic
- rbf neural network
- pid controller
- real time control
- condition monitoring
- convergence speed
- wireless sensor networks
- control system
- network architecture
- denoising
- pid control