引入优先因子的模糊Petri网及其在故障诊断中的应用

Fuzzy Petri Net Introducing Priority Factor and Its application to Fault Diagnosis

针对复杂系统故障机理的错综复杂,利用模糊产生式规则建立了模糊Petri网的故障诊断模型.一方面利用Petri网的图形描述能力,用分步运算加判断的方法在图形结构上进行正向或反向搜索;另一方面考虑实际故障搜索过程中,当同一层次上几个变迁的可信度值十分接近甚至相等时,仅依据可信度最大的原则来进行取舍的不合理性,引入表示故障严重程度的优先因子,使模型更符合实际情形.最后以某复杂系统故障诊断实例说明了模型的有效性.

Aiming at the complicated fault mechanism of complex systems, the fault diagnosis model is constructed using the fuzzy Petri net and priority factors. On one hand, it makes use of the function of graphics depiction, searching in positive or inverted direction step by step. On the other hand, when the values of certainty factors are approximately equivalent or even equivalent, only taking the values of certainty factors into account is obviously unreasonable. So the priority factor representing the severity degree of fault is introduced. Finally the model proposed has been applied to fault diagnosis of some complex systems, which proves the advantage of this model.