Analog circuit fault diagnosis based on artificial neural network and embedded system

Author

Peng, Kaixiang ; Dong, Lie ; Li, Fengjun

Author_Institution

Inf. Eng. Sch., Univ. of Sci. & Technol. Beijing, Beijing, China

Volume

1

fYear

2009

fDate

5-6 Dec. 2009

Firstpage

271

Lastpage

274

Abstract

Analog circuit fault diagnosis system based on S3C2410 embedded board is achieved in this paper. The hardware and software design are presented. Momentum addition BP neural network algorithm with embedded system is applied to that system. Real-time data collection and on-line detection of analog circuit fault condition are designed as the basic functions in the embedded system. Diagnosis system of intelligence and minimization is realized actually.

Keywords

analogue circuits; artificial intelligence; backpropagation; electronic engineering computing; embedded systems; neural nets; BP neural network algorithm; S3C2410 embedded board; analog circuit fault diagnosis; artificial neural network; data collection; embedded system; hardware design; software design; Analog circuits; Artificial neural networks; Circuit faults; Electrical fault detection; Embedded system; Fault detection; Fault diagnosis; Hardware; Real time systems; Software design; ARM; BP; Qt; analog circuit fault diagnosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Test and Measurement, 2009. ICTM '09. International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-4699-5

Type

conf

DOI

10.1109/ICTM.2009.5412941

Filename

5412941