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

Julwan Purba, Jie Lu, Da Ruan, Guangquan Zhang, Jan Wagemans

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
Volume2
StatePublished - Jun 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 Artifical Intellignece (LNAI)
Number6113

Conference

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

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