Primary-Auxiliary Statistical Local Kernel Principal Component Analysis and Its Application to Incipient Fault Detection of Nonlinear Industrial Processes.
Xiaogang DengPeipei CaiJiawei DengYuping CaoZhihuan SongPublished in: IEEE Access (2019)
Keyphrases
- fault detection
- industrial processes
- kernel principal component analysis
- kernel pca
- discriminant analysis
- fault diagnosis
- principal components
- feature extraction
- principal component analysis
- kernel function
- condition monitoring
- preprocessing
- kernel methods
- feature space
- high dimensional
- fault detection and diagnosis
- kernel matrix
- fault detection and isolation
- classification method
- high dimensional feature space
- linear discriminant analysis
- face recognition
- dimensionality reduction
- power plant
- machine learning
- support vector machine svm
- feature vectors
- pattern recognition
- subspace methods
- feature selection
- decision support system
- knowledge base
- decision making
- artificial intelligence