Analog Circuits Fault Diagnosis Using Support Vector Machine

摘要：

Support Vector Machine (SVM) is a machine learning algorithm based on statistical theory, which has advantages of simple structure and strong generalization ability as well as classification ability to a few samples. A new method of analog circuit fault diagnosis based SVM is presented in this paper. The method of circuit fault signatures selection is introduced and the model of analog circuit fault based SVM is obtained. The simulation results of a biquadratic filter testified that the proposed approach for analog circuit fault diagnosis is superior to conventional ones and is to increase the fault diagnosis accuracy.

作者: Yongkui Sun Guangju Chen Hui Li

作者单位: School of Automation Engineering University of Electronic Science and Technology of China Chengdu 61 School of Mechatronics Engineering University of Electronic Science and Technology of China Chengdu

会议类型: 国际会议

会议名称: 2007年通信、电路与系统国际会议(2007 International Conference on Communications,Circuits and Systems Proceedings)

会议地点: 日本福冈

会议语种:英文

在线出版日期: 2007-07-11（万方平台首次上网日期，不代表论文的发表时间）