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A Petri-Net Based Reasoning Procedure for Fault Identification in Sequential Operations

机译:基于Petri网的顺序操作故障识别推理程序

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摘要

In implementing any hazard analysis method, there is a need to reason deductively for identifying all possible fault origins that could lead to an undesirable consequence. Due to the complex time-variant cause-and-effect relations between events and states in sequential operations, the manual deduction process is always labor intensive and often error-prone. The theme of the present study is thus concerned mainly with the development of Petri-net based reasoning algorithms for automating such cause-finding procedures. The effectiveness and correctness of this approach are demonstrated with a realistic example in this paper.
机译:在实施任何危害分析方法时,需要进行演绎推理,以识别所有可能导致不良后果的故障根源。由于顺序操作中事件和状态之间复杂的时变因果关系,因此手动演绎过程总是劳动密集型的,并且往往容易出错。因此,本研究的主题主要涉及基于Petri网的推理算法的开发,该算法可自动执行此类原因查找程序。本文以一个实际的例子证明了这种方法的有效性和正确性。

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