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实现模拟电路高诊断率的方法

Method for Fulfilling High Rate of Fault Diagnosed in Analog Circuit

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【作者】 金瑜陈光肖飞

【Author】 Jin Yu 1) Chen Guangju 1) Xiao Fei 2) 1)(School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 610054) 2)(School of Electronic Engineering,University of Electronic Science and Technology of China,Chengdu 610054)

【机构】 电子科技大学自动化工程学院电子科技大学电子工程学院

【摘要】 针对神经网络诊断模拟电路故障中可能存在误诊这一不足,从多分辨分析理论出发,将一维小波的尺度函数和小波函数进行张量积,把得到的张量积小波的尺度函数和小波函数共同作为网络的激励函数,构造了一种小波神经网络,并用该小波神经网络诊断实例模拟电路.仿真结果表明,该小波神经网络不仅能够诊断出已训练的故障类型,而且还能对新故障进行正确的分类,避免了误诊情况的出现.

【Abstract】 The application of conventional neural network in analog circuit fault diagnosis might lead to false diagnosis.A wavelet neural network is proposed according to multiresolution analysis theory.Firstly,constructing tensor product scaling function and tensor product wavelet function according to the theory of tensor product;then the tensor product scaling function and wavelet are adopted as the activation functions for wavelet network.The proposed wavelet neural network is applied in analog circuit fault diagnosis.Experimental results show that this wavelet neural network can exactly diagnose those faults which have been trained.Furthermore,it can classify new faults exactly.Therefore,it can avoid the problem of false diagnosis.

【基金】 教育部新教师基金(20070614034)
  • 【文献出处】 计算机辅助设计与图形学学报 ,Journal of Computer-Aided Design & Computer Graphics , 编辑部邮箱 ,2008年10期
  • 【分类号】TP183;TN710
  • 【被引频次】2
  • 【下载频次】88
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