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

Yi Feng Wang, Chuei Tin Chang

Research output: Contribution to journalConference articlepeer-review

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.

Original languageEnglish
Pages (from-to)1265-1272
Number of pages8
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2773 PART 1
Publication statusPublished - 2003 Dec 1
Event7th International Conference, KES 2003 - Oxford, United Kingdom
Duration: 2003 Sep 32003 Sep 5

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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