A methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery.
Fannia PachecoMariela CerradaRené-Vinicio SánchezDiego CabreraChuan LiJosé Valente de OliveiraPublished in: LA-CCI (2016)
Keyphrases
- fault diagnosis
- rotating machinery
- statistical tests
- fault detection
- machine learning
- methodological framework
- statistical methods
- expert systems
- neural network
- statistically significant
- statistical analysis
- fault detection and diagnosis
- gas turbine
- machine learning algorithms
- bp neural network
- analog circuits
- model selection
- electronic equipment
- fuzzy logic
- chemical process
- industrial systems
- power transformers
- multi sensor information fusion
- operating conditions
- machine learning methods
- statistical models
- statistical model
- monitoring and fault diagnosis
- condition monitoring
- fault identification
- computational intelligence
- artificial intelligence
- data mining