TY - JFULL
AU - Abdelaziz Zaidi and Belkacem Ould Bouamama and Moncef Tagina
PY - 2011/1/
TI - Bond Graph and Bayesian Networks for Reliable Diagnosis
T2 - International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering
SP - 1749
EP - 1763
EM - Abdelaziz.Zaidi@isetso.rnu.tn, Belkacem.Ouldbouamama@polytech-lille.fr, Moncef.Tagina@ensi.rnu.tn
VL - 5
SN - 1307-6892
UR - http://waset.org/publications/8968
PU - World Academy of Science, Engineering and Technology
NX - International Science Index 60, 2011
N2 - Bond Graph as a unified multidisciplinary tool is widely
used not only for dynamic modelling but also for Fault Detection and
Isolation because of its structural and causal proprieties. A binary
Fault Signature Matrix is systematically generated but to make the
final binary decision is not always feasible because of the problems
revealed by such method. The purpose of this paper is introducing a
methodology for the improvement of the classical binary method of
decision-making, so that the unknown and identical failure signatures
can be treated to improve the robustness. This approach consists of
associating the evaluated residuals and the components reliability data
to build a Hybrid Bayesian Network. This network is used in two
distinct inference procedures: one for the continuous part and the
other for the discrete part. The continuous nodes of the network are
the prior probabilities of the components failures, which are used by
the inference procedure on the discrete part to compute the posterior
probabilities of the failures. The developed methodology is applied
to a real steam generator pilot process.
ER -