Influence of Time-frequency Diagram Aggregation and Fault Mechanism on CNN-based Bearing Fault Diagnosis Accuracy.
Zheng GongQiang LiuXiuzhi HeXiaoqin ZhouRongqi WangPublished in: SAFEPROCESS (2023)
Keyphrases
- fault diagnosis
- monitoring and fault diagnosis
- fault detection
- neural network
- expert systems
- operating conditions
- fault detection and diagnosis
- fuzzy logic
- multiple faults
- bp neural network
- chemical process
- condition monitoring
- power transformers
- rbf neural network
- rotating machinery
- industrial systems
- tennessee eastman
- multi sensor information fusion
- steam turbine
- fault identification
- fault detection and isolation
- failure diagnosis
- gas turbine
- analog circuits
- electronic equipment
- fault tree
- electrical power systems
- fault diagnostic
- fault isolation
- industrial processes
- vibration signal
- power plant
- autoregressive
- denoising