Diagnositic Knowledge Representation and Reasoning Based on Fuzzy Fault Petri Nets

Fei Liu, Jiansheng Hu, Jiannan Li
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引用次数: 1

Abstract

The core of fault diagnosis expert system is diagnostic knowledge representation and reasoning. Fuzzy Petri nets (FPN) have been testified to an ideal tool for knowledge representation and reasoning. However, when using FPN for diagnostic knowledge representation and reasoning, fault symptoms will disappear after fault propagated. This is not congruous with factual fault propagation. Another major limitation is the lacking of formal reasoning algorithm of FPN, which leads to it can't be implemented expediently by computer. In view of the limitations of FPN based diagnostic knowledge representation and reasoning, an enhanced model named fuzzy fault Petri nets (FFPN) and its formal reasoning algorithm are presented in the paper. A fault diagnosis instance was used to verify the feasibility and validity of the proposed method. It is demonstrated that this method is quite effective.
基于模糊故障Petri网的诊断知识表示与推理
故障诊断专家系统的核心是诊断知识表示和推理。模糊Petri网(FPN)已被证明是一种理想的知识表示和推理工具。然而,当使用FPN进行诊断知识表示和推理时,故障症状会在故障传播后消失。这与事实错误传播是不一致的。FPN的另一个主要限制是缺乏形式化的推理算法,这导致它不能方便地在计算机上实现。针对基于FPN的诊断知识表示和推理的局限性,提出了一种改进的模糊故障Petri网(FFPN)模型及其形式化推理算法。通过故障诊断实例验证了该方法的可行性和有效性。结果表明,这种方法是非常有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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