Ghedadba N, Hambaba L, Ayachi A, Aberkane MC, Bousselsela H, Oueld-Mokhtar SM.
Polyphénols totaux, activités antioxydante et antimicrobienne des extraits des feuilles de Marrubium deserti de Noé. PhytothérapiePhytothérapie. 2015;13 :118-129.
Ghedadba N, Hambaba L, Ayachi A, Aberkane MC, Bousselsela H, Oueld-Mokhtar SM.
Polyphénols totaux, activités antioxydante et antimicrobienne des extraits des feuilles de Marrubium deserti de Noé. PhytothérapiePhytothérapie. 2015;13 :118-129.
Rouabhi R, Abdessemed R, Chouder A, Djerioui A.
Power QualityEnhancement of Grid Connected Doubly-Fed Induction Generator Using Sliding Mode Control. International Review of Electrocal Engineering (IREE)International Review of Electrocal Engineering (IREE). 2015;10.
Rouabhi R, Abdessemed R, Chouder A, Djerioui A.
Power QualityEnhancement of Grid Connected Doubly-Fed Induction Generator Using Sliding Mode Control. International Review of Electrocal Engineering (IREE)International Review of Electrocal Engineering (IREE). 2015;10.
Rouabhi R, Abdessemed R, Chouder A, Djerioui A.
Power QualityEnhancement of Grid Connected Doubly-Fed Induction Generator Using Sliding Mode Control. International Review of Electrocal Engineering (IREE)International Review of Electrocal Engineering (IREE). 2015;10.
Rouabhi R, Abdessemed R, Chouder A, Djerioui A.
Power QualityEnhancement of Grid Connected Doubly-Fed Induction Generator Using Sliding Mode Control. International Review of Electrocal Engineering (IREE)International Review of Electrocal Engineering (IREE). 2015;10.
CHIREMSEL Z, NAIT-SAID R, CHIREMSEL R.
Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network. J Fail. Anal. and PrevenJ Fail. Anal. and Preven. 2015 :747–760.
AbstractSafety 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.
CHIREMSEL Z, NAIT-SAID R, CHIREMSEL R.
Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network. J Fail. Anal. and PrevenJ Fail. Anal. and Preven. 2015 :747–760.
AbstractSafety 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.
CHIREMSEL Z, NAIT-SAID R, CHIREMSEL R.
Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network. J Fail. Anal. and PrevenJ Fail. Anal. and Preven. 2015 :747–760.
AbstractSafety 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.