Reliability data for improvement of decision-making in Analytical Redundancy Relations Bond Graph based diagnosis

The method of Bond Graph based Analytical Redundancy Relations in Fault Detection and Isolation is explicitly associated with components faults, this is due to architectural and functional aspect of the Bond Graph tool. This allows using the reliability of each component to improve the decision-making step. The purpose of this paper is the improvement of the classical binary method of decision-making, so that it can treat unknown and identical signatures of failures. This approach consists of associating the measured residuals and the components reliability data to build a Hybrid Bayesian Network. This network is used to determine the posterior probabilities of the failures. As application, the approach is simulated on a controlled two-tank system.