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基于多小波变换的模拟电路IDDT故障诊断
引用本文:林美琴,陈艳峰.基于多小波变换的模拟电路IDDT故障诊断[J].计算机工程与应用,2009,45(23):239-241.
作者姓名:林美琴  陈艳峰
作者单位:华南理工大学 电子与信息学院,广州 510640
基金项目:广东省自然科学基金(the Natural Science Foundation of Guangdong Province of China under Grant No.31445)
摘    要:动态电源电流测试(IDDT)对模拟电路故障诊断非常有效。针对小波神经网络在模拟电路IDDT故障诊断中存在的缺陷,提吐了一种基于多小波变换的模拟电路IDDT故障诊断方法。即利用多小波变换提取电源电流各频段的能量,作为神经网络的输入特盘向量进行故障诊断。仿真结果表明,该方法是有效的,而且比小波神经网络方法的收敛速率快。

关 键 词:模拟电路  多小波变换  多小波神经网络  故障诊断
收稿时间:2008-4-28
修稿时间:2008-7-21  

Fault diagnosis in analog circuits IDDT based on multiwavelet transform
LIN Mei-qin,CHEN Yan-feng.Fault diagnosis in analog circuits IDDT based on multiwavelet transform[J].Computer Engineering and Applications,2009,45(23):239-241.
Authors:LIN Mei-qin  CHEN Yan-feng
Affiliation:College of Electronic and Information,South China University of Technology,Guangzhou 510640,China
Abstract:Dynamic supply current test is very useful for fault diagnosis in analog circuits.In order to improve the defect of wavelet neural network in fault diagnosis in analog circuits IDDT ,a method of fault diagnosis in analog circuits IDDT based on multiwavelet neural network is proposed.Multiwavelet transform is used to extract each frequency’s energy of current of power supply.Then the energy is used as input vector of neural network for fault diagnosis.Simulation results indicate that this method is effective,multiwavelet neural network converges more rapidly than wavelet neural network.
Keywords:analog circuits  multiwavelet transform  multiwavelet neural network  fault diagnosis
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