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From a functional graph to a T-timed Petri Nets model for the diagnosis of complex system

机译:从功能图到T定时Petri网模型,用于复杂系统的诊断

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In this paper, we are interested in the monitoring of complex systems modeled by functional graphs. We propose a diagnostic algorithm to isolate and identify the causes of failure located at a node of the functional graph. We establish hypotheses, first, on the choice of type of function who causes failure, and second, on the choice of the number of function who are directly observable. The key contribution of our approach is the establishment of behavioral models based on T-timed Petri Nets to refine the diagnosis based on functional graphs and to finally isolate faults. This study proposes first a generic model for representing the behavior of nodes in the functional graph according to a number of rules. These rules are designed to combine the partial models to form a global model based on a functional graph structure.
机译:在本文中,我们有兴趣监控功能图建模的复杂系统。我们提出了一种诊断算法来隔离并识别位于功能图的节点的故障原因。我们建立假设,首先是选择函数类型,导致失败,而第二,关于直接可观察的功能的选择。我们的方法的主要贡献是基于T-Timed Petri网的行为模型建立了基于功能图的诊断,并最终隔离故障。本研究提出了根据许多规则来提出用于表示功能图中的节点行为的通用模型。这些规则旨在将部分模型组合在一起基于功能图结构形成全局模型。

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