Optimizing kernel methods to reduce dimensionality in fault diagnosis of industrial systems.
José Manuel Bernal de LázaroAlberto Prieto MorenoOrestes Llanes-SantiagoAntônio José da Silva NetoPublished in: Comput. Ind. Eng. (2015)
Keyphrases
- industrial systems
- fault diagnosis
- kernel methods
- feature space
- industrial applications
- neural network
- high dimensional feature space
- kernel matrix
- expert systems
- kernel function
- fault detection
- support vector machine
- computational intelligence
- rbf neural network
- support vector
- fuzzy logic
- complex systems
- bp neural network
- multiple faults
- machine learning
- fault detection and diagnosis
- reproducing kernel hilbert space
- rotating machinery
- monitoring and fault diagnosis
- high dimensional
- power transformers
- analog circuits
- operating conditions
- condition monitoring
- kernel pca
- intelligent systems
- kernel matrices
- chemical process
- dimensionality reduction
- power plant
- gas turbine
- electronic equipment
- artificial intelligence
- real time
- clustering algorithm
- multi sensor information fusion