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Zhao, W.Q., Zhu, Y.L., Jiang, B., et al. (2008) Condition Assessment for Power Transformers by Bayes Networks. High Voltage Technology, 5, 1032-1039.

has been cited by the following article:

  • TITLE: Transformer’s Condition Assessment Method Based on Combination of Cloud Matter Element and Principal Component Analysis

    AUTHORS: Qianli Hong, Jiantao Zhang, Qing Xie, Shaodong Liang, Yuqin Xu, Si Li, Weitao Hu

    KEYWORDS: Transformer, Assessment Method, Principle Component Analysis, Cloud Model

    JOURNAL NAME: Energy and Power Engineering, Vol.9 No.4B, April 6, 2017

    ABSTRACT: With the development of power grid, as one of the key equipment, the transformer’s condition assessment method has always receive attention from experts, scholars concern more and more about the method’s practicality and reliability. In the traditional condition assessment method, due to the characteristics of the transformer’s complex structure, the assessment system is not comprehensive enough, or the assessment system is too complex, the indexes are not easy to quantify, such problems are emerging. The traditional method is complex and the degree of quantification is not enough. Therefore it is necessary to propose a condition assessment method that is easy to carry out the condition assessment work and does not affect the assessment results. In this paper, we propose a method to assess the state of the transformer’s complex structure. First, we establish a comprehensive assessment system, then apply the method of principal component analysis to optimize the index system, and then use the theory of cloud-matter-element. Finally the reliability and rationality of the method are verified by an example.