Condition detection of transformer winding based on entropy weight correlation theory
Guochao Qian, Huaitong Yin, Dexu Zou
Available Online November 2016.
- https://doi.org/10.2991/aest-16.2016.77How to use a DOI?
- transformer; winding; vibration frequency response; entropy weight correlation; condition detection.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/aest-16.2016.77 ID - Qian2016/11 ER -