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Signed directed graph-based hierarchical modelling and fault propagation analysis for large-scale systems

机译:大型系统基于有向图的有向图分层建模与故障传播分析

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摘要

The signed directed graph (SDG) model can be considered as a qualitative model to describe the variables and their cause-effect relations in a continuous process. Such models can allow one to obtain the fault propagation paths using the method of graph search. In this way, the authors can use SDGs to model and analyse the propagation of faults in large-scale industrial systems. However, with increasing system scales, the time requirements of a graph search method would be too onerous. This can be alleviated by transforming a single-layer SDG model into a hierarchical model to improve search efficiency. The hierarchical model would be composed of three layers: the top layer would consist of independent sub-systems; the middle layer would have control systems configuration and the bottom layer would have all the variables. The possible root causes of faults can then be searched in this model, layer by layer according to the initial response of the system. The efficacy of the proposed approach is illustrated by application to a four-tank system and a generator system in a power plant. The methodology presented here can also be used in process hazard analysis.
机译:可以将有向有向图(SDG)模型视为描述连续过程中变量及其因果关系的定性模型。这样的模型可以允许使用图搜索的方法获得故障传播路径。这样,作者就可以使用SDG对大型工业系统中的故障传播进行建模和分析。但是,随着系统规模的增加,图形搜索方法的时间要求将过于繁琐。可以通过将单层SDG模型转换为分层模型以提高搜索效率来缓解这种情况。层次模型将由三层组成:顶层将由独立的子系统组成;中间层将具有控制系统配置,而底层将具有所有变量。然后可以在该模型中根据系统的初始响应逐层搜索可能的故障根本原因。通过应用于发电厂的四缸系统和发电机系统,说明了所提出方法的有效性。这里介绍的方法还可以用于过程危害分析。

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