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Research on Fault Diagnosis of Civil Aircraft Based on AFPN

机译:基于AFPN的民用飞机故障诊断研究

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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.
机译:随着在民用飞机的故障诊断中的知识是动态和不确定的,提出了一种基于自适应模糊Petri网(APFN)的方法来解决问题。 AFPN不仅采取模糊Petri网的描述性优势,而且还具有像神经网络等学习能力。通过这种含义,首先使用模糊生产规则建立模糊的Petri网。然后由BP学习算法训练模糊Petri网的参数。最后,当模糊Petri网的重量固定时,可以通过故障推断找到故障原点。在本文末尾,旨在证明该方法在模糊推理中是可行的和有效的。

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