A Comparison of Two Feature-Based Ensemble Methods for Constructing Motor Pump Fault Diagnosis Classifiers.
Marcelo V. de OliveiraEstefhan Dazzi WandekokemEduardo MendelFábio FabrisFlávio Miguel VarejãoThomas W. RauberRodgrigo BatistaPublished in: ICTAI (1) (2010)
Keyphrases
- fault diagnosis
- ensemble methods
- ensemble learning
- majority voting
- individual classifiers
- decision trees
- condition monitoring
- ensemble classifier
- classifier ensemble
- machine learning methods
- prediction accuracy
- neural network
- random forests
- benchmark datasets
- expert systems
- base learners
- ensemble pruning
- fault detection
- base classifiers
- chemical process
- generalization ability
- operating conditions
- multiple faults
- bootstrap sampling
- fault detection and diagnosis
- gas turbine
- feature subset
- multi sensor information fusion
- fuzzy logic
- monitoring and fault diagnosis
- power transformers
- random forest
- support vector
- bp neural network
- analog circuits
- training set
- feature selection
- naive bayes
- training data
- machine learning algorithms
- induction motor
- test set
- support vector machine
- genetic algorithm
- data mining