A hybrid approach for fault tree analysis combining probabilistic method with fuzzy numbers

Julwan H. Purba, Jie Lu, Da Ruan, Guangquan Zhang

    Research outputpeer-review

    Abstract

    Fault tree analysis (FTA) is widely used for safety analysis of large and complex engineering systems such as nuclear power plants. Since FTA utilizes failure rate of every individual basic event constructing the tree, safety analysts have to provide probabilistic failure rate of every basic event in advance. However, it is often very difficult to exactly estimate the probability failure rates due to insufficient data, environment changing or new components. Fuzzy numbers can be applied to overcome the limitations of conventional FTA to predict the failure rate of basic events by handling linguistic terms. This study proposes a hybrid framework called Fuzzy Technique – based Fault Tree Analysis (FTFTA) to solve the problem and describes its procedures using a case study for emergency core cooling system of a typical nuclear reactor.
    Original languageEnglish
    Title of host publicationArtificial Intelligence and Soft Computing
    Place of PublicationHeidelberg, Germany
    Pages194-201
    Number of pages8
    Volume2
    EditionPART 1
    DOIs
    StatePublished - 2010
    EventICAISC 2010 - 10th International Conference on Artificial Intelligence and Soft Computing - ICAISC, Zakopane
    Duration: 13 Jun 201017 Jun 2010

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 1
    Volume6113 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceICAISC 2010 - 10th International Conference on Artificial Intelligence and Soft Computing
    Country/TerritoryPoland
    CityZakopane
    Period2010-06-132010-06-17

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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