Analog circuit fault diagnosis method based on CPSO-SVM

Author

Wang, Jianchen ; Shan, Ganlin ; Zhang, Qilong ; Duan, Xiusheng

Author_Institution

Dept. of Opt. & Electron. Eng., Shijiazhuang Mech. Eng. Coll., Shijiazhuang, China

fYear

2011

fDate

17-19 June 2011

Firstpage

465

Lastpage

468

Abstract

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.

Keywords

analogue circuits; chaos; circuit analysis computing; fault diagnosis; feature extraction; filters; particle swarm optimisation; support vector machines; CPSO-SVM; analog circuit fault diagnosis method; chaos theory; fault signal recognition; feature extraction; filter circuit; particle swarm optimization; support vector machine; Analog circuits; Chaos; Circuit faults; Fault diagnosis; Optimization; Particle swarm optimization; Support vector machines; analog circuit; chaos particle swarm optimization; fault diagnosis; support vector machine; wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2011 International Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4577-1229-6

Type

conf

DOI

10.1109/ICQR2MSE.2011.5976654

Filename

5976654