Multi component fault diagnosis of rotational mechanical system based on decision tree and support vector machine.
M. SaimuruganK. I. RamachandranV. SugumaranN. R. SakthivelPublished in: Expert Syst. Appl. (2011)
Keyphrases
- fault diagnosis
- multi component
- support vector machine
- decision trees
- decision forest
- training data
- machine learning
- neural network
- training set
- fault detection
- expert systems
- fuzzy logic
- fault detection and diagnosis
- feature vectors
- rbf neural network
- bp neural network
- chemical process
- naive bayes
- multiple faults
- rotating machinery
- failure diagnosis
- support vector machine svm
- power transformers
- support vector
- analog circuits
- non stationary
- fault identification
- condition monitoring
- monitoring and fault diagnosis
- multi sensor information fusion
- industrial systems
- electronic equipment
- operating conditions
- electrical power systems
- support vector regression
- radial basis function
- fault detection and isolation
- knn
- feature selection
- cost sensitive
- kernel function
- real time
- simulation model
- computational intelligence
- feature space