一种基于模糊神经网络的模拟电路故障诊断方法

提出了一种采用小波分析与遗传算法相结合的模糊神经网络对模拟电路进行故障诊断的新方法。该方法采用基于小波分析的主成分分析方法对网络的训练样本进行预处理，提取优化向量后利用遗传算法对模糊神经网络进行训练。对两个模拟电路的诊断实例表明该方法故障覆盖率高，并能有效诊断出同类方法误诊的故障类型。

Fuzzy Neural Network Based Analog Circuit Fault Diagnosis Using Genetic Algorithms

A systematic approach combining fuzzy neural network, wavelet analysis and genetic algorithm was proposed for fault diagnosis of analogue circuits.The presented fuzzy neural network was developed with the improved fuzzy weighted reasoning method. The optimal feature sets was extracted to train the network by using wavclet analysis as a preprocessor.This can ensure a simple architecture for the neural network and minimize the size of the training set required for its proper training. And the adjusting of connection weights and optimization of membership functions were performed with genetic algorithms. The reliability of this method was experimented with active filter examples.The resups of experimental tests show that this method can satisfactorily detect and identify the faults. It not only distinguishes the ambiguity sets or some misclassificd faults that some other methods cannot identify, but also has faster speed in the training of network.