Analog Circuit Fault Diagnosis Based on Wavelet Transform and Improved Fuzzy Support Vector Machine

摘要：

　　To improve the accuracy of analog circuit fault diagnosis,the method of combination wavelet transform and improved fuzzy support vector machine(FSVM) is presented in this paper based on the characteristics of wavelet transform and FSVM.The optimum eigenvector is proposed based on extracting wavelet power spectrum of the signal of analog circuit,whilst the membership function of FSVM is improved.Then the proposed approach is applied to diagnose the analog circuit fault,the experimental results show that the diagnosis accuracy of analog circuit fault is improved by proposed algorithm,and the algorithm is a feasible method for analog circuit fault.

关键词： Analog circuit fault diagnosis wavelet transform fuzzy support vector machine

作者: Li Baochen Tong Rui Ma Long Zhang Xiaoliang

作者单位: Ordnance Engineering College, Shijiazhuang 050003, China Wuhan Mechanical Technology College, Wuhan 430075, China

会议类型: 国际会议

会议名称: 2016 2nd International Conference on Mechanical, Electronic and Information Technology Engineering(2016机械、电子和信息技术国际会议)

会议地点: 重庆

会议语种:英文

页码: 331-336

在线出版日期: 2016-03-21（万方平台首次上网日期，不代表论文的发表时间）