%0 Journal Article
%T Analog circuit fault diagnosis based on particle swarm optimization SVM<br>基于粒子群算法优化支持向量机的模拟电路诊断
%A HU Yun-yan
%A PENG Min-fang
%A TIAN Cheng-lai
%A TAN Hu
%A SONG Li-wei
%A SHEN Mei-e
%A <br>胡云艳
%A 彭敏放
%A 田成来
%A 谭　虎
%A 宋丽伟
%A 沈美娥
%J 计算机应用研究
%D 2012
%I 
%X In order to improve the ccuracy of analog circuit fault diagnosis using support vectou machine SVMnetwork, this paper proposed the method based on particle swarm optimizationPSO and SVM. It preprocessed the response signals of the analog circuit using multiwavelet transform and obtained the optimal fault feature with better classification capacity using energy normalization. Then, after training the SVM by PSO, inputted the features into the ensemble SVM to identify different fault cases. Simulation results indicate that this method can effectively enhance the analog fault diagnostis accuracy.
%K fault diagnosis
%K analog circuit
%K particle swarm optimization
%K multiwavelet transform
%K support vector machine（SVM）<br>故障诊断
%K 模拟电路
%K 粒子群
%K 多小波变换
%K 支持向量机
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=11CC05D77ABBCF658B3894BBE5DE46AF&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=708DD6B15D2464E8&sid=82CB0081CB86F6A7&eid=3FBB3BBC131760C7&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=16