Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

The Analysis of Characteristics of Aviation AC Series Fault Arc

Authors
Feng Zhong, Junmin Zhang
Corresponding Author
Feng Zhong
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.27How to use a DOI?
Keywords
Arc fault; Fault detection; Wavelet transform; Wavelet energy; Information entropy.
Abstract

The AC series fault arc tests are conducted by a self-design platform according to several common test standards for fault arc circuit breakers in this paper. Compared with the no-arc current waveform, the current of fault circuit has shoulders when the current passes zero, and the current of fault circuit is lower than the no-arc current. A united method of the wavelet transform (WT) and the information entropy (IE) is proposed to distinguish the fault and normal circuit. By the WT of arc current and the analysis of multiple-sampling, the results reveal that the arc fault frequency bands (FB) range is (625, 1250) Hz. The wavelet component D3 of arc current and its wavelet energy (WE) have large value during the arc period. The wavelet energy of no-arc circuit is lower than 0.006. The IE is bigger than 1 in the fault circuit. Therefore, the FB, WE, IE can be chosen as the fault characteristics to detect the fault circuits.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.27How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Feng Zhong
AU  - Junmin Zhang
PY  - 2016/11
DA  - 2016/11
TI  - The Analysis of Characteristics of Aviation AC Series Fault Arc
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 148
EP  - 153
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.27
DO  - https://doi.org/10.2991/aiea-16.2016.27
ID  - Zhong2016/11
ER  -