Semi-Supervised Fuzzy C-Means Clustering Optimized by Simulated Annealing and Genetic Algorithm for Fault Diagnosis of Bearings.
Jianbin XiongXi LiuXingtong ZhuHongbin ZhuHaiying LiQinghua ZhangPublished in: IEEE Access (2020)
Keyphrases
- fault diagnosis
- fuzzy c means clustering
- genetic algorithm
- simulated annealing
- semi supervised
- condition monitoring
- fuzzy logic
- neural network
- fault detection
- fuzzy c means
- genetic algorithm ga
- expert systems
- vibration signal
- fault detection and diagnosis
- evolutionary algorithm
- power transformers
- pairwise
- clustering method
- electronic equipment
- bp neural network
- chemical process
- operating conditions
- rotating machinery
- gas turbine
- supervised learning
- analog circuits
- monitoring and fault diagnosis
- multi sensor information fusion
- particle swarm optimization
- artificial neural networks
- data mining
- power plant
- membership functions
- computational intelligence
- multiple faults
- multiscale
- cluster analysis
- unsupervised learning
- edge detection
- active learning
- image segmentation