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Journal of Failure Analysis and Prevention

, Volume 16, Issue 5, pp 747–760 | Cite as

Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network

  • Zakarya Chiremsel
  • Rachid Nait Said
  • Rachid Chiremsel
Technical Article---Peer-Reviewed

Abstract

Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.

Keywords

SIS Fault tree Bayesian network Decision tree Model-based diagnosis Evidence Diagnostic importance factor 

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Copyright information

© ASM International 2016

Authors and Affiliations

  • Zakarya Chiremsel
    • 1
  • Rachid Nait Said
    • 1
  • Rachid Chiremsel
    • 2
  1. 1.IHSI-LRPIUniversity of Batna 2BatnaAlgeria
  2. 2.Department of Computer ScienceUniversity of Batna 2BatnaAlgeria

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