Fault detection, identification, and reconstruction of faulty chemical gas sensors under drift conditions, using Principal Component Analysis and Multiscale-PCA.
Marta PadillaAlexandre PereraIvan MontoliuA. ChaudryKrishna C. PersaudSantiago MarcoPublished in: IJCNN (2010)
Keyphrases
- principal component analysis
- fault detection
- fault diagnosis
- multiscale
- principal components
- industrial processes
- dimensionality reduction
- dimension reduction
- fault identification
- operating conditions
- covariance matrix
- independent component analysis
- condition monitoring
- face recognition
- feature extraction
- linear discriminant analysis
- tennessee eastman
- face images
- low dimensional
- feature space
- failure detection
- genetic algorithm
- fault detection and diagnosis
- fault detection and isolation
- robust fault detection
- negative matrix factorization
- real time
- fuel cell
- image processing
- random projections
- singular value decomposition
- kernel pca
- wavelet transform
- fine scale
- fault localization
- expert systems
- lower dimensional
- image segmentation
- fault isolation
- circuit board
- linear discriminate analysis
- model based diagnosis
- genetic programming
- computational intelligence
- machine learning
- neural network