Résumé

The article focuses on the decision making in fault diagnosis of lubri-cation systems. In these systems, the diagnosis covers, in the majority of cases, the mechanical reliability or analysis of lubricating oils, but in a separate man-ner. In this section, the mechanical reliability is considered in combination with the lubricant quality, but the diagnosis process is always infected by uncertain-ties. Bayesian network (BN) model is developed and used as a decision-making tool. From this one, it is possible to quantify the probability of failure of this system. The diagnosis of failures is based on using Fault-Tree (FT) and Baye-sian Network (BN). Firstly, a conversion from FT to BN is presented to estab-lish a quick and accurate diagnosis. Secondly, the diagnosis is optimized by means of Influence Diagram (ID) which measures the preference.

Information

Item Type:	BookChapter
Divisions:	» Faculté des Sciences et de la Technologie
ePrint ID:	1730
Date Deposited:	2019-05-10
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/fr/publication/article/1730

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