Comparative Study on Two New Analog Circuit Fault Diagnosis Methods

DOI

10.2991/icmcs-18.2018.67How to use a DOI?

Keywords

Wavelet transform; BP neural network; Analogous circuit; Fault diagnosis

Abstract

Analog circuits are widely used in various fields. With the increasing complexity of electronic systems, the maintenance of electronic circuits is particularly important. The analog circuit is influenced by its own nonlinearity and environment interference, and the system fault types are complex and diverse. Therefore, finding an effective fault diagnosis method is very important. Based on this, this paper analyzes the characteristics of wavelet transform and neural network fault diagnosis methods through simulation experiments, verifies the feasibility of the two methods to identify faults, and provides experience guidance for future fault diagnosis.

Copyright

© 2018, 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  - Tao Wang
AU  - Wen Sun
PY  - 2018/10
DA  - 2018/10
TI  - Comparative Study on Two New Analog Circuit Fault Diagnosis Methods
BT  - Proceedings of the 8th International Conference on Management and Computer Science (ICMCS 2018)
PB  - Atlantis Press
SP  - 332
EP  - 335
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmcs-18.2018.67
DO  - 10.2991/icmcs-18.2018.67
ID  - Wang2018/10
ER  -