Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)

Transformer winding modal parameter identification based on poly-reference least-square complex frequency domain method

Authors
Yaning Li, Hong Yu, Xiaoyan Zhu
Corresponding Author
Yaning Li
Available Online November 2016.
DOI
10.2991/aest-16.2016.107How to use a DOI?
Keywords
transformer; winding; modal parameters; PolyMAX.
Abstract

The modal parameter of transformer winding, as direct reflections of mechanical performance, is an important theoretical foundation in the field of transformer manufacturing and detection of winding condition based on vibration. To identify the modal parameters accurately, a modal experiment on a 10 kV transformer winding was conducted in this paper. A PolyMAX method to identify winding natural frequency and damping ratio was proposed using the experiment to identify transformer winding modal parameters. And it uses modal confidence criterion to verify. The first four order modal parameters, including natural frequency, damping ratio were extracted from the vibration signal. The results demonstrate that all the natural frequencies are far from two times of exciting frequency, which indicates that the design is appropriate. The parameters verifies by MAC, which verifies the effectiveness of the proposed method in identifying modal parameters of transformer windings.

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 International Conference on Advanced Electronic Science and Technology (AEST 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
10.2991/aest-16.2016.107
ISSN
1951-6851
DOI
10.2991/aest-16.2016.107How 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  - Yaning Li
AU  - Hong Yu
AU  - Xiaoyan Zhu
PY  - 2016/11
DA  - 2016/11
TI  - Transformer winding modal parameter identification based on poly-reference least-square complex frequency domain method
BT  - Proceedings of the 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016)
PB  - Atlantis Press
SP  - 796
EP  - 803
SN  - 1951-6851
UR  - https://doi.org/10.2991/aest-16.2016.107
DO  - 10.2991/aest-16.2016.107
ID  - Li2016/11
ER  -