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Reliability analysis of multi-state system with common cause failure based on bayesian networks

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Warianty tytułu
PL
Analiza niezawodności systemu wielostanowego z uszkodzeniem spowodowanym wspólną przyczyną w oparciu o sieci bayerowskie
Języki publikacji
EN
Abstrakty
EN
Taking account of the influence of common cause failure (CCF) to system reliability and the widespread presence of multi-state system (MSS) in engineering practices, a method for reliability modeling and assessment of a multi-state system with common cause failure is proposed by taking the advantage of graphic representation and uncertainty reasoning of Bayesian Network (BN). The model is applied to a two-axis positioning mechanism transmission system to demonstrate its effectiveness and capability for directly calculating the system reliability on the basis of multi-state probabilities of components. Firstly, the reliability block diagram is built according to the hierarchy of structure and function of multi-state system. Then, the traditional Bayesian Networks model of the transmission system is constructed based on the reliability block diagram, failure logic between components and the failure probability distribution of them. In this paper, the β-factor model is used to analyze the CCF of the transmission system, and a new Bayesian network combining with CCF is established following by the implementation of reliability analysis. Finally, the comparison between the proposed method and the one without considering CCF is made to verify the efficiency and accuracy of the proposed method.
PL
Uwzględniając wpływ uszkodzeń spowodowanych wspólną przyczyną (CCF) na niezawodność systemów oraz powszechne występowanie w praktyce inżynierskiej systemów wielostanowych (MSS), zaproponowano metodę modelowania i oceny niezawodności systemu wielostanowego z uszkodzeniem spowodowanym wspólną przyczyną, która wykorzystuje reprezentację graficzną sieci Bayesa (BN) i oparte na nich wnioskowanie przybliżone. Model zastosowano do analizy układu przenoszenia napędu dwu-osiowego mechanizmu pozycjonowania. Zbadano w ten sposób skuteczność modelu oraz możliwość wykorzystania go do bezpośredniego obliczania niezawodności systemu na podstawie wielostanowych prawdopodobieństw elementów składowych. W pierwszej kolejności stworzono schemat blokowy niezawodności uwzględniający hierarchię struktury i funkcji badanego systemu wielostanowego. Następnie, w oparciu o schemat blokowy niezawodności, logikę uszkodzeń komponentów oraz rozkład prawdopodobieństwa uszkodzeń tych komponentów, skonstruowano tradycyjny model bayesowski układu przenoszenia napędu. W niniejszej pracy wykorzystano model współczynnika β do analizy CCF układu przenoszenia napędu oraz opracowano nową sieć Bayesa uwzględniającą CCF, po czym przeprowadzono na ich podstawie analizę niezawodności. Skuteczność i dokładność proponowanej metody sprawdzono poprzez porównanie jej z metodą nie wykorzystującą CCF.
Rocznik
Strony
169--175
Opis fizyczny
Bibliogr. 32 poz.
Twórcy
autor
autor
autor
autor
autor
  • School of Mechanical, Electronic, and Industrial Engineering University of Electronic Science and Technology of China No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, Sichuan, 611731 P. R. China, hzhuang@uestc.edu.cn
Bibliografia
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  • 21. Ramirez-Marquez JE, Coit D V. Composite Importance Measures for Multi-State Systems with Multi-State Components. IEEE Transactions and Reliability 2005; 54: 517–529.
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  • 24. Warren CG. Common causes failures: Implementation of a simplified alpha factor model. Reliability and Maintainability Symposium 2010; 1–5.
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  • 30. Zhou ZB, Jin G, Dong D, Zhou J. Reliability analysis of multistate systems based on Bayesian networks. 13th Annual IEEE International Conference and Workshop on Engineering of Computer Based Systems (ECBS 2006), 2006.
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  • 32. Zhou ZB, Ma CQ, Zhou JL. Application of Bayesian networks reliability analysis of Binary-state system with multi-state components.Journal of Harbin Institute of Technology 2009; 41: 232–235.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT6-0015-0017
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