Bayesian network for fault diagnosis

Fault diagnosis based on artificial intelligence techniques often deals with uncertain knowledge and incomplete input data. Probability reasoning is a method to deal with uncertain information, and Bayesian network is a tool that brings it into the real world applications. This paper describes the application of Bayesian network for diagnosing faulty components from engineered systems. A general procedure for constructing the Bayesian network structure on the basis of a bond graph model is proposed. We demonstrate how the resulting Bayesian network can be applied to fault diagnosis in an engineered system.