A novel LDA-based approach for motor bearing fault detection.
Lucio CiabattoniGionata CiminiFrancesco FerracutiAlessandro FreddiGianluca IppolitiAndrea MonteriùPublished in: INDIN (2015)
Keyphrases
- fault detection
- fault diagnosis
- industrial processes
- linear discriminant analysis
- fault identification
- latent dirichlet allocation
- topic models
- failure detection
- tennessee eastman
- fuel cell
- fault detection and diagnosis
- condition monitoring
- robust fault detection
- rotating machinery
- face recognition
- fault localization
- pattern recognition
- fault isolation
- fault detection and isolation
- machine learning
- expert systems
- feature extraction
- principal component analysis
- management system
- control system
- computer simulation
- generative model
- computational intelligence
- feature space