Title :
Analog Circuits Fault Diagnosis Based on Support Vector Machine
Author :
Yongkui, Sun ; Guangju, Chen ; Hui, Li
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
In this paper a new method for diagnosing analog circuits fault based support vector machine (SVM) is presented. The fault features are extracted from the frequency domain response of circuit under test (CUT) and the SVM which trained by the fault features is used to recognize and classify the unknown faults. Support vector machine is simple in architecture and strong generalization ability. The experimental results show that the proposed method for diagnosing analog circuits fault based on SVM correctly classifies faulty components with more than 99% accuracy.
Keywords :
analogue circuits; circuit testing; fault diagnosis; support vector machines; analog circuits diagnosis; circuit under test; fault diagnosis; fault features; support vector machine; Analog circuits; Artificial neural networks; Circuit faults; Circuit testing; Fault diagnosis; Feature extraction; Instruments; Neural networks; Support vector machine classification; Support vector machines; analog circuits; fault diagnosis; support vector machine;
Conference_Titel :
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-1136-8
Electronic_ISBN :
978-1-4244-1136-8
DOI :
10.1109/ICEMI.2007.4350996
