Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)

Transformer insulation aging assessment and life prediction based on a variety characteristics

Authors
Xun Wan, Kunyu Tan, Yun Liu, Huisheng Ye, Shihua Zhao, Ping Peng, Minfang Peng
Corresponding Author
Xun Wan
Available Online November 2016.
DOI
https://doi.org/10.2991/icmia-16.2016.118How to use a DOI?
Keywords
transformer;life prediction;insulation aging assessment;variety characteristics
Abstract

In order to make the transformer insulation aging assessment and life prediction more reasonable, we established transformer evaluation model based on the operating load, environmental factors, the electrical characteristics of the experiment and oil chromatographic characteristics. Then we applied the evaluation model to the engineering practice and the prediction result is satisfactory.

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 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-256-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/icmia-16.2016.118How 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  - Xun Wan
AU  - Kunyu Tan
AU  - Yun Liu
AU  - Huisheng Ye
AU  - Shihua Zhao
AU  - Ping Peng
AU  - Minfang Peng
PY  - 2016/11
DA  - 2016/11
TI  - Transformer insulation aging assessment and life prediction based on a variety characteristics
BT  - Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-16.2016.118
DO  - https://doi.org/10.2991/icmia-16.2016.118
ID  - Wan2016/11
ER  -