Improving the analysis of dependable systems by mapping fault trees into Bayesian networks
Improving the analysis of dependable systems by mapping fault trees into Bayesian networks
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DOI：
10.1016/s0951-8320(00)00077-6
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发表时间：
2001-03-01
影响因子：
8.1
通讯作者：
Ciancamerla, E
中科院分区：
文献类型：
--
作者：
Bobbio, A;Portinale, L;Ciancamerla, E
贝叶斯网络（BN）提供了一种鲁棒的概率推理方法。它们已经成功地应用于各种现实世界的任务，但它们在可靠性领域很少受到关注。本文旨在探讨BN形式主义在可靠系统分析中的能力。为此，本文将BN与大型安全关键系统可靠性分析的最流行技术之一，即故障树（FT）进行了比较。本文表明，任何FT可以直接映射到BN和基本的推理技术，后者可以用来获得经典的参数计算从前者（即可靠性的顶部事件或任何子系统，关键部件等）。此外，通过使用BN，可以在建模和分析级别获得一些额外的功效。在建模层面，可以去除FT方法中隐含的几个限制性假设，并可以容纳组件之间的各种依赖关系。在分析级别，可以执行一般诊断分析。这两种方法的比较进行了一个运行的例子，从文献中，由一个冗余的多处理器系统。(C)2001爱思唯尔科技有限公司版权所有。
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of dependability. The present paper is aimed at exploring the capabilities of the BN formalism in the analysis of dependable systems. To this end, the paper compares BN with one of the most popular techniques for dependability analysis of large, safety critical systems, namely Fault Trees (FT). The paper shows that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc). Moreover, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. At the modeling level, several restrictive assumptions implicit in the FT methodology can be removed and various kinds of dependencies among components can be accommodated. At the analysis level, a general diagnostic analysis can be performed. The comparison of the two methodologies is carried out by means of a running example, taken from the literature, that consists of a redundant multiprocessor system. (C) 2001 Elsevier Science Ltd. All rights reserved.