Journal of Frontiers of Computer Science and Technology ›› 2017, Vol. 11 ›› Issue (6): 1006-1013.DOI: 10.3778/j.issn.1673-9418.1603013

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Bidirectional Fuzzy Fault Reasoning Algorithm of Intuitionistic Fuzzy Petri Net

SUN Xiaoling+   

  1. School of Mathematics and Statistics, Hefei Normal University, Hefei 230601, China
  • Online:2017-06-01 Published:2017-06-07



  1. 合肥师范学院 数学与统计学院,合肥 230601

Abstract: According to the complicated uncertain relation between fault phenomenon and fault reason in fault diagnosis, using the advantage of intuitionistic fuzzy sets in expressing uncertainty information and the ability of graphics  processing of Petri net, this paper presents a bidirectional fuzzy fault diagnosis inference algorithm based on intuitionistic fuzzy Petri nets. The reverse intuitionistic fuzzy reasoning algorithm is firstly applied to the model reduction in order to find the cause of the fault. The positive intuitionistic fuzzy reasoning algorithm is used to calculate the model and then output the results. The algorithm can not only simplify the fault information and reduce the time complexity of the inference process, but also can improve the fault diagnosis degree of certainty. Automobile engine diagnosis shows that the bidirectional intuitionistic fuzzy reasoning algorithm is feasible and effective.

Key words: intuitionistic fuzzy Petri nets, intuitionistic fuzzy reasoning, fault diagnosis, bidirectional fuzzy fault reasoning

摘要: 针对故障诊断中故障现象与故障原因之间复杂的不确定关系,利用直觉模糊集表达不确定性信息的优势和Petri网的图形处理问题的能力,给出了基于直觉模糊Petri网的双向模糊故障推理算法。该算法首先利用反向直觉模糊推理算法对模型进行约减,查找故障原因,再利用正向直觉模糊推理算法对模型进行计算,输出结果。该算法既可将故障信息化繁为简,降低推理过程的时间复杂度,还能够使故障诊断的确定性程度得到进一步提高。汽车发动机诊断案例表明了所给双向直觉模糊推理算法的可行性和有效性。

关键词: 直觉模糊Petri网, 直觉模糊推理, 故障诊断, 双向模糊故障推理