Condition detection of transformer winding based on entropy weight correlation theory

DOI

10.2991/aest-16.2016.77How to use a DOI?

Keywords

transformer; winding; vibration frequency response; entropy weight correlation; condition detection.

Abstract

To effectively detect the hidden fault of transformer winding, the combination of grey correlation analysis and entropy weight theory is proposed to detect the winding condition of power transformer based on the inherent relations of vibration frequency response (VFR) curves of several measured points. The vibration frequency response experiment is made on a real 220kV transformer winding both in normal and loosened conditions. The grey correlation degree and grey area correlation degree of VFR curves in each measured point. Then the entropy weight correlation degree is defined to determine the weight value of all the obtained features. The results have shown that the detection results based on the proposed method are agreed well with the preset condition of transformer winding, which is better illustrated the loosened degree of transformer winding. Compared with the existed FRA method, the vibration frequency response method is more sensitive to the variations of winding condition and has high application value.

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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TY  - CONF
AU  - Guochao Qian
AU  - Huaitong Yin
AU  - Dexu Zou
PY  - 2016/11
DA  - 2016/11
TI  - Condition detection of transformer winding based on entropy weight correlation theory
BT  - Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)
PB  - Atlantis Press
SP  - 569
EP  - 580
SN  - 1951-6851
UR  - https://doi.org/10.2991/aest-16.2016.77
DO  - 10.2991/aest-16.2016.77
ID  - Qian2016/11
ER  -