Issue |
E3S Web Conf.
Volume 260, 2021
2021 International Conference on Advanced Energy, Power and Electrical Engineering (AEPEE2021)
|
|
---|---|---|
Article Number | 02013 | |
Number of page(s) | 5 | |
Section | Power Electronics Technology and Application | |
DOI | https://doi.org/10.1051/e3sconf/202126002013 | |
Published online | 19 May 2021 |
Method of building transformer acoustic diagnosis database based on multi physical field coupling modeling
1 Anhui Xiangshuijian Pumped Storage Co. LTD, Wuhu, Anhui, 241083, China
2 North China Electric Power University, Beijing, 102206, China
* Corresponding author: 1269567697@qq.com
In this paper, a method of building dynamic acoustic diagnosis database of dry-type transformer is proposed. The method is mainly combined with collecting the basic noise of transformer and simulating the acoustic signals of transformer under different working conditions to improve the fault database of transformer. Due to the incomplete working conditions on site, the simulated working conditions are relatively complete, and the marked acoustic signal file is generated, and then form the composition of the database. This paper focuses on the finite element simulation analysis of transformer vibration and noise radiation based on COMSOL, and the idea of establishing transformer biological diagnosis database. Improve the efficiency of transformer fault design and research, and provide reliable and convenient data services for researchers.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.