Nonlinear set-membership identification and fault detection using a Bayesian framework: Application to the wind turbine benchmark.
Rosa M. Fernández-CantíSebastian Tornil-SinJoaquim BlesaVicenç PuigPublished in: CDC (2013)
Keyphrases
- bayesian framework
- fault detection
- posterior probability
- generative model
- prior knowledge
- machine learning
- control system
- fault diagnosis
- probability density function
- industrial processes
- high quality
- state space
- image processing
- maximum a posteriori
- decision making
- artificial intelligence
- real time
- prior distribution
- tennessee eastman