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ON THE EXACT ANALYSIS OF NON-COHERENT FAULT TREES: THE ASTRA PACKAGE

机译:关于非相干故障树的确切分析:Astra包

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Fault Tree Analysis (FTA) is widely used for safety and more recently, for security studies. Depending on the type of variables fault trees can be Coherent/Non-Coherent and the corresponding structure functions are monotonic/non-monotonic. Apart from Event Trees (ET) analyzed using the fault tree linking approach, non coherent fault trees have never been particularly popular among practitioners, in spite of their usefulness in system modeling. This was due to the lack of powerful analysis methods, which has led to the use of procedures applied to the approximated coherent tree. However, these procedures work well only if components' failure probability are "sufficiently" low, i.e. when the success probability can reasonably be approximated to unity. A very efficient approach to FTA is based on Binary Decision Diagrams (BDD) Bryant [1], Brace et al. [2]. A BDD is a compact graph representation of Boolean functions. The Binary Decision Diagrams (BDD) approach applied to FTA offers several advantages e.g. it works equally well on coherent and non-coherent trees, it offers the possibility to perform the exact probabilistic analysis without the need to determine the system failure modes (Minimal Cut Sets, MCS, or Prime Implicants PI) Rauzy [3], Rauzy and Dutuit [4]. Different algorithms have been proposed in the past for the probabilistic quantification of non-coherent fault trees. These algorithms can be classified in two groups. The first encompasses algorithms that determine the system unconditional failure and repair frequencies, directly from the set of Prime Implicants, whereas algorithms of the second group determine them on the basis of the probability of system's critical states. For example, Inagaki and Henley [5] and Liu and Pan [6] proposed methods belonging to the first group, whereas the methods proposed by Becker and Camarinopoulos [7] and Beeson and Andrews [8] belong to the second group. Moreover the problem of determining the importance of components in non-coherent trees has been tackled among the other, by Jackson [9], Zhang and Mei [10] and Beeson and Andrews [8]. All these methods, when applied to the set of Prime Implicants, represented in the form of SOP (Sum of Products) or in the form of DSOP (Disjunctive SOP) of Prime Implicants, are very time consuming, hence bound approximations and/or cut off techniques are necessarily to be applied.
机译:故障树分析(FTA)广泛用于安全性,最近用于安全研究。根据变量的类型,故障树可以是连贯的/不相干的,并且相应的结构功能是单调/非单调。除了使用故障树链接方法分析的活动树(et)分析的情况下,尽管他们在系统建模方面有用,但非相干故障树从未在从业者中特别流行。这是由于缺乏强大的分析方法,这导致使用应用于近似的相干树的程序。然而,只有当组件的失败概率“充分”低电平时,这些程序才能很好地工作,即当成功概率可以合理地近似于单位时。对FTA的非常有效的方法是基于二进制决策图(BDD)Bryant [1],Brace等。 [2]。 BDD是布尔函数的紧凑型图形表示。应用于FTA的二进制决策图(BDD)方法提供了几个优点。它同样适用于连贯和非相干的树木,它提供了在没有确定系统故障模式(最小剪切,MC或PI)Rauzy [3],Rauzy和Hairs责任容[4]。过去已经提出了不同的算法,用于非相干故障树的概率量化。这些算法可以分为两组。第一个包括直接从一组主要血管集中确定系统无条件故障和修复频率的算法,而第二组的算法基于系统关键状态的概率确定它们。例如,Inagaki和Henley [5]和Liu和Pan [6]属于第一组的提出方法,而Becker和Camarinopoulos [7]和Beeson和Andrews [8]提出的方法属于第二组。此外,在另一个,杰克逊[9],张和梅[10]和蜂师和安德鲁斯在另一个,Zhang和Mei [10]中,确定了在非相干树中的重要性的问题。所有这些方法,当应用于以SOP形式(产品之和)的形式或以DSOP(探测SOP)的形式或垂直于素血管的形式表示时,非常耗时,因此约束近似和/或切割关闭技术必须应用。

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