Abstract

This paper presents a model for predicting the risk of failure of gas turbine control and
protection system. Using a traditional analysis method and an artificial intelligence method, we
combined Fault Tree Analysis (FTA) with a Bayesian Network (BN) to obtain accurate results for
system failures. While the Fault Tree Analysis allows us to know the causes that lead to the system
failure, by listing the information available in the fault tree in addition to the data previously stored by the experts, the Bayesian Network method allows us to quantify the impact of each cause on the gas turbine control and protection system, to take corrective actions to prevent them from happening in the future.

Information

Item Type:	Conference
Divisions:	» Laboratory of Research on Electromechanical and Dependability » Faculty of Science and Technology
ePrint ID:	4057
Date Deposited:	2023-05-26
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/4057

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