Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

On-line Monitoring of Electrical Equipment and Fault Diagnosis Analysis

Authors
Jian-wei Zhao
Corresponding Author
Jian-wei Zhao
Available Online March 2016.
DOI
https://doi.org/10.2991/icmmct-16.2016.14How to use a DOI?
Keywords
On-line monitoring; Fault diagnosis; Potential transformer; BP neural network.
Abstract
In order to improve the reliability of power system, on-line monitoring and fault diagnosis for electrical equipment is very necessary. In this paper, we research on-line monitoring and fault diagnosis of transformer, building the gas online monitoring system in transformer oil, and improved transformer fault diagnosis -characteristic gas method through the BP neural network. Through gas on-line monitoring of transformer oil, and the example verification, improved diagnosis method is effective for transformer fault diagnosis.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
https://doi.org/10.2991/icmmct-16.2016.14How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jian-wei Zhao
PY  - 2016/03
DA  - 2016/03
TI  - On-line Monitoring of Electrical Equipment and Fault Diagnosis Analysis
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 70
EP  - 74
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.14
DO  - https://doi.org/10.2991/icmmct-16.2016.14
ID  - Zhao2016/03
ER  -