%0 Journal Article
%T Analog circuit fault identification approach based on wavelet analysis and hierarchical decision<br>基于小波分析和分层决策的模拟电路故障识别方法
%A SONG Guo-ming
%A WANG Hou-jun
%A JIANG Shu-yan
%A LIU Hong
%A <br>宋国明
%A 王厚军
%A 姜书艳
%A 刘红
%J 计算机应用研究
%D 2010
%I 
%X Aiming at overlapped recognition on analog circuit fault diagnosis with large number of fault categories, this paper presented a fault identification approach based on wavelet analysis and hierarchical decision. Firstly, extracted two types of fault features of circuit under test by using wavelet transform. Then processed clustering analysis for fault feature data sets by fuzzy C-mean algorithm, which separated fault sub-classes in form of decision tree. Partitioned the fault sub-classes maximally by optimizing the feature selection on each tree node. Finally, constructed a hierarchical fault decision system by combining multiple classifiers according to the structure of decision tree. Chose support vector machines and neural networks as classifiers for tree nodes to validate the proposed method and improved the fault identification accuracy effectively. The experimental results on a high-pass filter are higher than 99%, which is better than classical support vector machine methods.
%K analog circuits
%K fault diagnosis
%K wavelet transform
%K fuzzy C-mean algorithm
%K hierarchical decision<br>模拟电路
%K 故障诊断
%K 小波变换
%K 模糊C均值算法
%K 分层决策
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C140A87A3A9C59A838BCFAEFDD770FC8&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=B31275AF3241DB2D&sid=287DFAEA599AEAB7&eid=5F72C4E06FEFC1BD&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9