改进的模糊Petri网在民航飞机故障诊断中的应用

Application of Improved Fuzzy Petri Nets in Fault Diagnosis of Civil Aircraft

针对民航飞机系统的复杂性,采用了反正向推理相结合的模糊Petri网的故障诊断模型。首先,依据预设的变迁阈值,采用反向搜索策略,对建立好的模糊Petri网模型进行约简,以减小后续推理规模,提高推理搜索速度;然后采用正向推理算法进行数值计算,将复杂的推理过程通过矩阵运算实现,充分利用了模糊Petri网的并行处理能力,使模糊推理过程更加简单快速和易于实现;最后通过实例验证了该方法的有效性。

As the complexity of civil aircraft system has increased,a model of fault diagnosis based on fuzzy Petri nets and backward-forward reasoning algorithm is proposed.Firstly,the fuzzy Petri nets＇ model is reduced by applying the reverse search algorithm and the preset threshold,so as to reduce the subsequent reasoning scale and improve reasoning search speed.Secondly,the forward reasoning algorithm is used to calculate the real value of the fault so that this complicated reasoning process with matrix operation can be achieved.It demonstrates that the fuzzy reasoning process is accomplished more simply,quickly and easily as the algorithm is adopted and the efficiency of the reasoning is also improved due to the parallel operation ability of Petri net.Finally,a fault diagnosis example explains the validity of the method.