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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability >Qualitative Analysis of Complex Modularized Fault Trees Using Binary Decision Diagrams
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Qualitative Analysis of Complex Modularized Fault Trees Using Binary Decision Diagrams

机译：使用二元决策图对复杂模块化故障树进行定性分析

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摘要

Fault tree analysis is commonly used in the reliability assessment of industrial systems. When complex systems are studied conventional methods can become computationally intensive and require the use of approximations. This leads to inaccuracies in evaluating system reliability. To overcome such disadvantages, the binary decision diagram (BDD) method has been developed. This method improves accuracy and efficiency, because the exact solutions can be calculated without the requirement to calculate minimal cut sets as an intermediate phase. Minimal cut sets can be obtained if needed.BDDs are already proving to be of considerable use in system reliability analysis. However, the difficulty is with the conversion process of the fault tree to the BDD. The ordering of the basic events can have a crucial effect on the size of the final BDD, and previous research has failed to identify an optimum scheme for producing BDDs for all fault trees. This paper presents an extended strategy for the analysis of complex fault trees. The method utilizes simplification rules that are applied to the fault tree to reduce it to a series of smaller subtrees whose solution is equivalent to the original fault tree. The smaller subtree units are less sensitive to the basic event ordering during BDD conversion. BDDs are constructed for every subtree. Qualitative analysis is performed on the set of BDDs to obtain the minimal cut sets for the original top event. It is shown how to extract the minimal cut sets from complex and modular events in order to obtain the minimal cut sets of the original fault tree in terms of basic events.
机译：故障树分析通常用于工业系统的可靠性评估中。在研究复杂系统时，常规方法可能会占用大量计算资源，并且需要使用近似值。这导致评估系统可靠性的不准确性。为了克服这些缺点，已经开发了二进制决策图（BDD）方法。此方法提高了准确性和效率，因为可以计算出精确的解决方案，而无需将最小切割集计算为中间阶段。如果需要，可以获得最小的割集。BDD已被证明在系统可靠性分析中有相当大的用途。但是，困难在于故障树到BDD的转换过程。基本事件的排序可能会对最终BDD的大小产生关键影响，并且先前的研究未能找到为所有故障树生成BDD的最佳方案。本文提出了一种用于分析复杂故障树的扩展策略。该方法利用应用于故障树的简化规则，将其简化为一系列较小的子树，这些子树的解决方案与原始故障树等效。较小的子树单元在BDD转换期间对基本事件顺序不太敏感。为每个子树构造BDD。对这组BDD进行定性分析，以获得原始最高事件的最小割集。它显示了如何从复杂事件和模块化事件中提取最小割集，以便获得有关基本事件的原始故障树的最小割集。

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