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The Scientific World Journal
Volume 2015, Article ID 459268, 8 pages
http://dx.doi.org/10.1155/2015/459268
Research Article

A Dynamic Integrated Fault Diagnosis Method for Power Transformers

1Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
2State Grid Energy Research Institute, Beijing 102209, China
3Electric Power Research Institute, CSG, Guangzhou 510080, China

Received 5 August 2014; Revised 10 December 2014; Accepted 18 December 2014

Academic Editor: Martin Riera-Guasp

Copyright © 2015 Wensheng Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Yi Cui, Lakshitha Naranpanawe, and Junhyuck Seo, “Evolutionary Bayesian fusion for transformers fault detection,” 2016 Australasian Universities Power Engineering Conference (AUPEC), pp. 1–6, . View at Publisher · View at Google Scholar
  • Hui Ma, Tapan Saha, and Yi Cui, “Multi-source information fusion for power transformer condition assessment,” IEEE Power and Energy Society General Meeting, vol. 2016-, 2016. View at Publisher · View at Google Scholar
  • Lakshitha Naranpanawe, Yi Cui, and Junhyuck Seo, “Evolutionary Bayesian fusion for transformers fault detection,” Proceedings of the 2016 Australasian Universities Power Engineering Conference, AUPEC 2016, 2016. View at Publisher · View at Google Scholar
  • Xianbin Sun, Jiwen Tan, Yan Wen, and Chunsheng Feng, “Rolling bearing fault diagnosis method based on data-driven random fuzzy evidence acquisition and Dempster-Shafer evidence theory,” Advances In Mechanical Engineering, vol. 8, no. 1, 2016. View at Publisher · View at Google Scholar
  • Salah H. El-Hoshy, Osama E. Gouda, and Hassan H. El-Tamaly, “Proposed heptagon graph for DGA interpretation of oil transformers,” IET Generation, Transmission and Distribution, vol. 12, no. 2, pp. 490–498, 2018. View at Publisher · View at Google Scholar