Extending Fault Trees with Continuous System Variables

A. Karacaorenli, Luigi PORTINALE

Risultato della ricerca: Contributo alla conferenzaContributo in Atti di Convegnopeer review

Abstract

Fault Tree Analysis (FTA) is a widely adopted methodology where events are modeling the working/failure dichotomy of components and subsystems. However, system variables are often of continuous nature, and in some cases measured through a monitoring process. In this paper, we present an approach aimed at introducing continuous variables in a standard static fault tree (FT) formalism. We show how continuous variables can be tied to basic events in a FT, how to model probabilistic linear dependencies among them, and how influences of contextual information on system variables can be captured and modeled. We called the resulting formalism c-FT, and we propose a conversion of a c-FT into Hybrid Bayesian Networks (HBN); this allows us to exploit HBN inference algorithms, in order to perform the analyses of interest on the modeled system. As an experimental framework, we consider a model for a waste incinerator, and we present the results of specific analyses (from system reliability, to posterior probability of faulty situations) implemented through conversion of a c-FT into an HBN and by exploiting the MATLAB BNT Toolbox for inference.
Lingua originaleInglese
Numero di pagine8
Stato di pubblicazionePubblicato - 1 gen 2020
Evento30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference - Venice (Italy)
Durata: 1 gen 2020 → …

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???event.eventtypes.event.conference???30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference
CittàVenice (Italy)
Periodo1/01/20 → …

Keywords

  • Fault Trees
  • Bayesian Networks
  • Hybrid Bayesian Networks
  • Continuous Variables

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