论文标题
补救维护的因果链事件图
Causal chain event graphs for remedial maintenance
论文作者
论文摘要
系统可靠性的分析通常受益于故障树和贝叶斯网络等图形工具。在本文中，我们使用一个称为链事件图（CEG）的概率图形模型代替了常规的图形工具来表示系统的失败和过程。 CEG源自事件树，可以灵活地表示不对称过程的展开。对于此应用，我们需要定义一类新的正式干预措施，我们称补救措施为补救维护的因果关系建模。这样可以解决故障的根本原因，并将系统的状态返回到新的状态。我们证明，CEG的语义足以表达这种新型的干预类型。此外，通过定制因果代数，CEG提供了一个透明的框架，其中指导并表达了有关各种不同类型的补救干预效果的预测推断背后的基本原理。后门定理适用于这些干预措施，以帮助发现何时仅观察到系统。
The analysis of system reliability has often benefited from graphical tools such as fault trees and Bayesian networks. In this article, instead of conventional graphical tools, we apply a probabilistic graphical model called the chain event graph (CEG) to represent the failures and processes of deterioration of a system. The CEG is derived from an event tree and can flexibly represent the unfolding of asymmetric processes. For this application we need to define a new class of formal intervention we call remedial to model causal effects of remedial maintenance. This fixes the root causes of a failure and returns the status of the system to as good as new. We demonstrate that the semantics of the CEG are rich enough to express this novel type of intervention. Furthermore through the bespoke causal algebras the CEG provides a transparent framework with which guide and express the rationale behind predictive inferences about the effects of various different types of remedial intervention. A back-door theorem is adapted to apply to these interventions to help discover when a system is only partially observed.
