Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)

Research on Key Technology of Fault Diagnosis of Power Cables

Authors
Dandan Su, Dezhong Kong
Corresponding Author
Dandan Su
Available Online February 2017.
DOI
10.2991/meita-16.2017.98How to use a DOI?
Keywords
Power Cables, Fault Diagnosis, Neural Network
Abstract

With the expansion of city scale and the acceleration of the process of urban construction, the power cables plays more and more important role in the city network. At the same time, the increase of the number of cables and the continuous extension of the cable running time result in more and more frequent cable failures. This paper analyzes the common causes of the cable fault, and gives the key technology of the cable fault diagnosis to provide some references for the relative researchers.

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/).

Download article (PDF)

Volume Title
Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
Series
Advances in Engineering Research
Publication Date
February 2017
ISBN
978-94-6252-304-3
ISSN
2352-5401
DOI
10.2991/meita-16.2017.98How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - Dandan Su
AU  - Dezhong Kong
PY  - 2017/02
DA  - 2017/02
TI  - Research on Key Technology of Fault Diagnosis of Power Cables
BT  - Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
PB  - Atlantis Press
SP  - 473
EP  - 476
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-16.2017.98
DO  - 10.2991/meita-16.2017.98
ID  - Su2017/02
ER  -