基于Petri网故障诊断及在工程机械中的应用

Petri net based fault diagnosis method and its application in engineering machinery

针对传统模糊Petri网在故障诊断应用中的不足之处,提出了一种新的故障诊断模糊Petri网模型(FD-FPN),变迁激活概率元素的引入,使反向推理中冲突消解问题的解决更加合理。在此基础上,提出了基于变迁激活概率矩阵的反向推理算法,正向与反向推理方法的结合可以实现故障因果的相互验证,使故障诊断过程更加科学,结论更符合事实。最后,结合故障诊断实例的应用,证明了文中提出方法的合理性和有效性,且运算简单,便于计算机实现。

Based on the deficiencies of the traditional fuzzy Petri net applications to fault diagnosis,this paper puts forward a new Fuzzy Petri Net model of Fault Diagnosis（FD-FPN）.Because of change activation probability elements introduced,it is more reasonable that making reverse reasoning to solve the problem of conflict resolution.On that basis,the backward reasoning algorithm based on the change of activation probability matrix is proposed.The mutual validation causal fault is realized by combing with positive and reverse reasoning methods,making fault diagnosis process is more scientific and the conclusion is truer.Finally,combined with the application of fault diagnosis example,the proposed method is proved reasonable and effective in this paper,and it is convenient not only simple operation but also for realization by a computer.