Application of complete ensemble intrinsic time-scale decomposition and least-square SVM optimized using hybrid DE and PSO to fault diagnosis of diesel engines.
Junhong ZhangYu LiuPublished in: Frontiers Inf. Technol. Electron. Eng. (2017)
Keyphrases
- fault diagnosis
- bp neural network
- least squares
- neural network
- soft computing methods
- fault detection
- steam turbine
- electrical power systems
- support vector
- monitoring and fault diagnosis
- expert systems
- power system
- fault detection and diagnosis
- rotating machinery
- condition monitoring
- support vector machine
- particle swarm optimization
- support vector machine svm
- chemical process
- feature selection
- power transformers
- gas turbine
- analog circuits
- particle swarm optimization pso
- operating conditions
- rbf neural network
- optimization algorithm
- multiscale
- training data
- power plant
- particle swarm optimization algorithm
- complex systems
- back propagation
- fuzzy logic
- training set
- genetic algorithm