A petri-net based reasoning procedure for fault identification in sequential operations

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Abstract

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.

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Wang, Y. F., & Chang, C. T. (2003). A petri-net based reasoning procedure for fault identification in sequential operations. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2773 PART 1, pp. 1265–1272). Springer Verlag. https://doi.org/10.1007/978-3-540-45224-9_171

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