基于故障分类的故障树生成与分析

A. Tai, C. Walter, L. Fesq, J. Day
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引用次数: 1

摘要

在过去的几十年里,故障树作为一种可视化/交流媒体,以及构建可靠系统的定量分析工具,一直是从业者最广泛使用的故障管理(FM)机制之一。尽管如此,到目前为止,故障树分析通常无法为我们提供高可信度的结果,因为故障事件之间的关系可能存在误解。回顾过去,灾难性系统故障几乎总是由一系列混合故障表现和相互作用引起的。此外,FM本身的故障可能成为故障表现链中的关键因素。1996年阿丽亚娜5号火箭自毁给我们上了一堂关于不适当使用调频的毁灭性后果的课。这些先前的经验教训启发我们提出了一个故障类感知和fm能力感知的故障树分析框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault-class-aware fault tree generation and analysis
Over decades, fault-tree has remained as one of the most widely used fault management (FM) mechanisms by practitioners as a visualization/communication media, as well as a quantitative analysis tool for building dependable systems. Nonetheless, to date fault tree analysis is often unable to provide us with high-confidence results due to potential misrepresentation of the relationships among failure events. In retrospect, catastrophic system failures were almost always caused by a chain of mixed fault manifestation and interaction. Moreover, faults in FM itself may become a critical element in a fault-manifestation chain. The 1996 Ariane-5 rocket self-destruction provides us with a lesson on the devastating consequence of inappropriate FM application. Such prior lessons have inspired us to propose a fault-class-aware and FM-capability-aware fault tree analysis framework.
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