Analog Circuits Fault Diagnosis Based on Support Vector Machine

摘要：

in this paper a new method for diagnosing analog circuits fault based support vector machine (SVM) is presented. The fault features are extracted from the frequency domain response of circuit under test (CUT) and the SVM which trained by the fault features is used to recognize and classify the unknown faults. Support Vector Machine is simple in architecture and strong generalization ability. The experimental results show that the proposed method for diagnosing analog circuits fault based on SVM correctly classifies faulty components with more than 99％ accuracy.

关键词： analog circuits support vector machine fault diagnosis

作者: Sun Yongkui Chen Guangju Li Hui

作者单位: School of Automation Engineering,University of Electronics Science and Technology of China,Chengdu 6 School of Mechatronics Engineering,University of Electronics Science and Technology of China,Chengdu

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）