Increasing effectiveness of model-based fault diagnosis: A Dynamic Bayesian Network design for decision making

Philippe Weber (1) , Didier Theilliol (1) , Christophe Aubrun (1) , Alexandre Evsukoff (2)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 COPPE-UFRJ - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia

This papers aims to design a new approach in order to increase the performance of the decision making in model-based fault diagnosis when signature vectors of various faults are identical or closed. The proposed approach consists on taking into account the knowledge issued from the reliability analysis and the model-based fault diagnosis. The decision making, formalised as a bayesian network, is established with a priori knowledge on the dynamic component degradation through Markov chains. The effectiveness and performances of the technique are illustrated on a heating water process corrupted by faults.

Domaines: Automatique / Robotique

Philippe Weber, Didier Theilliol, Christophe Aubrun, Alexandre Evsukoff. Increasing effectiveness of model-based fault diagnosis: A Dynamic Bayesian Network design for decision making. 6th IFAC Symposium on Fault Detection, Supervision and Safety of technical processes, 2006, Beijing, China. pp.109-114. ⟨hal-00092023⟩