基于AFPN的民用飞机故障诊断研究

Xiuyan Wang, Binbin Xue, Zongshuai Li, J. Lin
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引用次数: 1

摘要

针对民用飞机故障诊断中知识的动态性和不确定性,提出了一种基于自适应模糊Petri网(APFN)的故障诊断方法。AFPN既具有模糊Petri网的描述性优点,又具有神经网络的学习能力。首先利用模糊产生规则建立模糊Petri网;然后用BP学习算法对模糊Petri网的参数进行训练。最后,当模糊Petri网的权值一定时,通过故障推理可以找到故障的根源。最后通过实验验证了该方法在模糊推理中的可行性和有效性。
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Research on Fault Diagnosis of Civil Aircraft Based on AFPN
As the knowledge in the fault diagnosis of civil aircraft is dynamic and uncertain, a method based on the Adaptive Fuzzy Petri Net(APFN) is proposed to solve the problem. AFPN not only takes the descriptive advantages of fuzzy Petri net, but also has learning ability like neural network. By this mean, firstly set up a fuzzy Petri net using the fuzzy production rule. Then the parameters of the fuzzy Petri net are trained by BP learning algorithm. At last, when the weights of the fuzzy Petri net are fixed, the fault origin can be found through the fault inference. At the end of the paper, an experiment is designed to demonstrate that the approach is feasible and effective in fuzzy reasoning.
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