Fault diagnosis of analog circuit based on support vector machines

Author

Liu, Yehui ; Yang, Yuye ; Huang, Liang

Author_Institution

Beijing Polytech. Coll., Beijing, China

fYear

2009

fDate

16-18 Oct. 2009

Firstpage

40

Lastpage

43

Abstract

An innovative method based on support vector machines is presented to diagnose the fault of analog circuit. Firstly, in order to get enough fault samples, the circuit program is compiled in MATLAB software to obtain expressions of output signals. Secondly, fault samples are sent into Support Vector Machines to train Support Vector Machines. Thirdly, the test samples are classified by trained Support Vector Machines. Finally, an example of analog circuit fault diagnosis is provided. The result shows that this method has the advantages of simple algorithm, high efficiency, high accuracy, great capability in generalization and classification.

Keywords

analogue circuits; circuit analysis computing; fault diagnosis; learning (artificial intelligence); support vector machines; MATLAB software; analog circuit; fault diagnosis; trained support vector machines; Analog circuits; Artificial neural networks; Circuit faults; Circuit testing; Fault diagnosis; MATLAB; Mathematical model; Pattern recognition; Support vector machine classification; Support vector machines; SVM; Support Vector Machines; analog circuit; fault diagnosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications Technology and Applications, 2009. ICCTA '09. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-4816-6

Electronic_ISBN

978-1-4244-4817-3

Type

conf

DOI

10.1109/ICCOMTA.2009.5349243

Filename

5349243