Assessment of steam turbine blade failure and damage mechanisms using a Bayesian network.
David A. Quintanar-GagoPamela F. NelsonÁngeles Díaz-SánchezMichael S. BoldrickPublished in: Reliab. Eng. Syst. Saf. (2021)
Keyphrases
- bayesian networks
- steam turbine
- input output
- operating conditions
- fault diagnosis
- student modeling
- graphical models
- learning bayesian networks
- artificial intelligence
- naive bayes
- mechanism design
- knowledge base
- decision trees
- damage detection
- structural learning
- machine learning
- structure learning
- damage assessment
- probabilistic inference
- probabilistic reasoning
- conditional independence
- influence diagrams
- incomplete data
- real time
- high speed
- multi class
- data sets