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本文提出了利用模糊神经网络进行模拟电路故障诊断的方法。该方法根据模式识别原理,利用建立在神经网络中的模糊特征库,推断出故障特征对各元件故障的隶属程度,并指示元件参数的变化趋势。这一方法为解决模拟电路及一些含有非线性元件的电路的故障诊断问题提供了一种新方法。
This paper presents a method of fault diagnosis of analog circuits using fuzzy neural network. According to the principle of pattern recognition, this method uses the fuzzy feature library based on neural network to deduce the degree of membership of fault features to each component fault and indicate the changing trend of component parameters. This method provides a new method to solve the problem of fault diagnosis of analog circuits and some circuits with non-linear components.