Research on Application of Embedded System Based on Neural Network in Analog Circuit Fault Diagnosis

DOI

10.2991/icemc-17.2017.143How to use a DOI?

Keywords

BP neural network; Analog circuit; Fault diagnosis; Simulation analysis

Abstract

With the rapid development of modern electronic technology, the circuit is highly integrated and large-scale, which leads to the complexity of circuit fault diagnosis. Based on this, a method put forward in this paper is to use BP neural network to diagnose the fault of analog circuits. According to the characteristics of neural network embedded system, a hard fault diagnosis system is designed and simulated. The simulation results show that the fault tolerance of analog circuits can be well recognized when the fault tolerance is about 5%.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wang Tao
PY  - 2016/06
DA  - 2016/06
TI  - Research on Application of Embedded System Based on Neural Network in Analog Circuit Fault Diagnosis
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Computer Science (ICEMC 2017)
PB  - Atlantis Press
SP  - 709
EP  - 713
SN  - 2352-538X
UR  - https://doi.org/10.2991/icemc-17.2017.143
DO  - 10.2991/icemc-17.2017.143
ID  - Tao2016/06
ER  -