Bayesian reliability models of Weibull systems: State of the art
Abdelaziz Zaidi ; Belkacem Ould Bouamama ; Moncef Tagina
International Journal of Applied Mathematics and Computer Science, Tome 22 (2012), p. 585-600 / Harvested from The Polish Digital Mathematics Library

In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation of the reliability model, Bayesian estimation of Weibull parameters and the model's goodness-of-fit are evoked. The advantages of this modelling approach are presented in the case of systems with an unknown reliability structure, those with a common cause of failures and redundant ones. Finally, we raise the issue of the use of BNs in the fault diagnosis area.

Publié le : 2012-01-01
EUDML-ID : urn:eudml:doc:244063
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Abdelaziz Zaidi; Belkacem Ould Bouamama; Moncef Tagina. Bayesian reliability models of Weibull systems: State of the art. International Journal of Applied Mathematics and Computer Science, Tome 22 (2012) pp. 585-600. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv22z3p585bwm/

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