基于直觉模糊Petri网的故障诊断

Fault diagnosis based on intuitionistic fuzzy Petri nets

故障诊断经常受到多种不确定性和模糊性因素的影响,针对不确定性的故障诊断问题,利用直觉模糊集较好的表达不确定性信息的优势和Petri网较好的并行处理以及图形处理问题的能力,构建了直觉模糊Petri网模型。由于将直觉模糊推理转化为矩阵运算的过程中有非隶属度参数的参与,因此推理结果可提供更多的信息。根据实际故障诊断中的模糊推理问题,给出了带有权值、阈值等参数条件下新的直觉模糊推理算法。通过获取和处理故障诊断中的不确定性和模糊性的知识,该算法将故障诊断过程转化为利用直觉模糊Petri网的直觉模糊推理过程。实际燃气轮机故障诊断模型案例表明了所给直觉模糊推理算法的有效性。

Fault diagnosis is often affected by many uncertain and fuzzy factors. In view of the uncer- tain fault diagnosis, an intuitionistic fuzzy Petri net model is constructed by considering that intuitionis- tic fuzzy sets can better express uncertainty information and Petri networks has strong parallel process- ing and graphics processing ability. Because non-membership parameters are involved when Intuitionistic fuzzy reasoning is transformed into matrix operations, the reasoning result can offer more information. According to the actual fuzzy inference problem in the process of fault diagnosis, a new fuzzy reasoning algorithm with weights, threshold value parameters is given. Through obtaining and processing the un- certain and fuzzy knowledge in the process of fault diagnosis, the algorithm converts the fault diagnosis to intuitionistic fuzzy reasoning by using intuitionistic fuzzy Petri nets. The actual gas turbine fault diag- nosis model shows that the intuitionistic fuzzy reasoning algorithm is effective.