用因果理论解析故障树，回答'为何出错'这一诊断核心问题。
Actual causality in fault trees
- 基于因果理论重构故障树，从'可能出错'转向'为何出错'
- 揭示最小割集如何生成实际因果，建立结构与因果的映射关系
- 适合系统故障诊断、安全分析领域的研究人员使用
故障树是复杂系统中广泛使用的有效风险模型，用于回答'什么可能出错？'，尤其通过最小割集分析实现。本文从Halpern & Pearl的实际因果理论视角研究故障树，使其能够回答'为何出错？'这一故障诊断的核心问题。我们对实际因果的不同概念进行了完整分类，依据故障树的图结构和逻辑结构，阐明了最小割集如何产生实际因果。
原文摘要 · Abstract (English)
Fault trees are a widely used as effective risk models for complex systems, answering the question "what can go wrong?", especially through minimal cut set analysis. We study fault trees from the perspective of Halpern & Pearl's theory of actual causality. This allows us to use fault trees to answer the question "why has it gone wrong?", which is fundamental to failure diagnostics. We give a complete classification of each of the different notions of actual causality in terms of the fault tree's graph structure and logical structure, and show how minimal cut sets give rise to actual causes.
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