Title :
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
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;
Conference_Titel :
Test and Measurement, 2009. ICTM '09. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4699-5
DOI :
10.1109/ICTM.2009.5412941
