A Bayesian network dealing with measurements and residuals for system monitoring. (April 2016) - Atoui, Mohamed Amine; Verron, Sylvain; Kobi, Abdessamad
The purpose of this paper is to present an original method for system monitoring with Bayesian networks. Our proposal is to associate a data-driven method to another model-based under a common tool. The two methods are first modeled under a Bayesian network (conditional Gaussian network), and then combined to evaluate the system state. In the proposed framework the residuals and measures coexist under a probabilistic framework. This approach is tested on a simulation of a water heater process under some various circumstances and shows better results than the two methods used alone.