Analog Circuit Fault Diagnosis Method Based on CPSO-SVM

被引：0

作者：

Wang, Jianchen ^{[1
]}

Shan, Ganlin ^{[1
]}

Zhang, Qilong ^{[1
]}

Duan, Xiusheng ^{[1
]}

机构：

[1] Shijiazhuang Mech Engn Coll, Dept Opt & Elect Engn, Shijiazhuang, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (ICQR2MSE) | 2011年

关键词：

analog circuit; fault diagnosis; support vector machine; chaos particle swarm optimization; wavelet analysis;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

To realize feature extraction and fault signal recognition efficiently in analog circuit fault diagnosis, a novel diagnosis method called CPSO-SVM is proposed. In this method, Chaos theory and Particle Swarm Optimization (PSO) are combined to form a new approach called CPSO and this approach is applied to the optimization of SVM parameters. A fault diagnosis experiment on a certain filter circuit indicates that the proposed diagnosis method is feasible and efficient.

引用

页码：465 / 468

页数：4

共 13 条

[1]

Albert B., 2002, 1 COURSE WAVELETS FO

[2]

[Anonymous], COMPUTER SCI

[3]

[Anonymous], P 1997 IEEE INT C SY, DOI DOI 10.1109/ICSMC.1997.637339

[4] Chaos Particle Swarm Optimization Applications in the TSP problem [J].

Chen Legeng ;

Wang Zhida ;

He Chuangyi .

THIRD INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING, 2009, :682-685

[5]

Gao S., 2006, Swarm intelligence algorithms and applications

[6]

Huang Jie, 2004, Microelectronics, V34, P21

[7]

[罗志勇 LUO Zhiyong], 2006, [计算机工程, Computer Engineering], V32, P34

[8]

Qi Li-mei, 2008, Journal of University of Electronic Science and Technology of China, V37, P386

[9]

Reddy B. R., 2009, P 2009 ANN REP C EL, P409

[10]

Vapnik V., 1995, The nature of statistical learning theory

← 1 2 →