Fault Diagnosis of Analogue Circuits Using Hyper-sphere SVM and AdaBoost

Author

Liu, Chong ; Zhang, Jundong ; Ren, Guang

Author_Institution

Marine Eng. Coll., Dalian Maritime Univ., Dalian, China

Volume

1

fYear

2009

fDate

12-14 Dec. 2009

Firstpage

11

Lastpage

14

Abstract

In order to solve the problems of correctly identifying fault classes in fault diagnosis of analogue circuit and improve classification ability, a fault diagnosis method for analog circuits based on AdaBoost algorithm and hypersphere support vector machine (hypersphere SVM) is developed in this paper. This algorithm uses Hyper-sphere SVMs as weak learners of AdaBoost and use AdaBoost algorithm to improve the accuracy of weak learners. Simulation results of diagnosing an analog circuit show us the proposed technique has the higher classification accuracy compared with support vector machine and has confirmed the validity of the method.

Keywords

analogue circuits; electronic engineering computing; fault diagnosis; support vector machines; AdaBoost algorithm; analogue circuits; fault classes; fault diagnosis method; hypersphere SVM; hypersphere support vector machine; Algorithm design and analysis; Analog circuits; Circuit faults; Circuit simulation; Computational intelligence; Design engineering; Educational institutions; Fault diagnosis; Support vector machine classification; Support vector machines; AdaBoost Algorithm; Fault diagnosis of analogue circuits; Hyper-sphere SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on

Conference_Location

Changsha

Print_ISBN

978-0-7695-3865-5

Type

conf

DOI

10.1109/ISCID.2009.10

Filename

5370951