Accurate bearing faults classification based on statistical-time features, curvilinear component analysis and neural networks.
Miguel DelgadoGiansalvo CirrincioneAntoni GarcíaJuan Antonio OrtegaHumberto HenaoPublished in: IECON (2012)
Keyphrases
- component analysis
- neural network
- classification accuracy
- pattern recognition
- feature vectors
- feature extraction
- feature set
- feature space
- fault diagnosis
- factor analysis
- gender classification
- training set
- pattern classification
- blind source separation
- supervised learning
- image classification
- text classification
- support vector
- image processing
- feature selection
- image features
- statistical analysis
- machine learning methods
- support vector machine
- statistical models
- training samples
- knn
- computer vision
- learning algorithm
- machine learning
- data mining