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author:

He, D.-H. (He, D.-H..) [1] | Cai, J.-D. (Cai, J.-D..) [2] | Xie, S. (Xie, S..) [3] | Zeng, Q.-M. (Zeng, Q.-M..) [4]

Indexed by:

Scopus

Abstract:

Return voltage method (RVM) is a good method to study aging state of transformer insulation, but it is difficult to accurately assess the insulation aging state by a single characteristic quantity. In this paper, the fuzzy rough sets theory combined with RVM is proposed to assess the oil paper insulation state of transformer and construct the assessment system of oil paper insulation of transformer based on a lot of test data. First, the evaluation index of oil-paper insulation status of transformer is established by return voltage characteristic parameters. Then, fuzzy c-means clustering algorithm is used to obtain the membership function of the transformer test data along with fuzzy partition of characteristics .Moreover, the fuzzy attributes of assessment table of oil paper insulation statue is simplified according to the distinct matrix,and it extracts the evaluation rule of oil paper insulation condition. Finally, the examples in this paper demonstrate that the assessment system is effective and feasible, which provides a new idea for the assessment of transformer oil-paper insulation state. The research has practical value in application of engineering. © 2016 The authors and IOS Press. All rights reserved.

Keyword:

Fuzzy C means clustering; Fuzzy rough sets; Return voltage

Community:

  • [ 1 ] [He, D.-H.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Cai, J.-D.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 3 ] [Xie, S.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [Zeng, Q.-M.]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • [He, D.-H.]College of Electrical Engineering and Automation, Fuzhou UniversityChina

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Source :

Frontiers in Artificial Intelligence and Applications

ISSN: 0922-6389

Year: 2016

Volume: 293

Page: 81-86

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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