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Fourier-Motzkin method for failure diagnosis in Petri Net models of discrete event systems

机译:离散事件系统的Petri网模型中的Fore-Motzkin方法

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This paper presents a new technique for failure diagnosis in partially observable discrete event systems modelled as Petri nets. In this new technique we adopt Integer Fourier-Motzkin Elimination (IFME) method. We start with a Petri net and produce the state equations. The state equations are a set of integer valued inequalities in variables that represent number of firing of transitions. Occurrences of failure can also be expressed by inequalities. Then we extend the set of inequalities obtained from the state equations to two new sets. The first is created from adding the inequality for failure. The second is created from adding the negation of the inequality for failure. Applying the IFME method to the two resulting sets of inequalities, the variables corresponding to unobservable transitions will be eliminated. Then we prove that for acyclic Petri nets, the reduced set of inequalities after the elimination can be used to diagnose failures.
机译:本文介绍了作为Petri网建模的部分可观察到的离散事件系统的失效诊断技术。在这种新技术中,我们采用整数傅里叶 - Motzkin消除(IFME)方法。我们从Petri网开始并产生状态方程。状态等式是一组变量中的整数值,其变量表示转换的射击次数。失败的发生也可以通过不等式表达。然后,我们将从状态方程获得的一组不等式扩展到两个新集。第一个是从添加失败的不等式创建。第二种是通过添加对失败不等式的否定来创建的。将IFME方法应用于两个产生的不等式集,将消除对应于不可观察的转换的变量。然后,我们证明,对于非循环培养网,消除后的减少的不平等程度可用于诊断失败。

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