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author:

Liu, R. (Liu, R..) [1] | Yang, T. (Yang, T..) [2] | He, Q. (He, Q..) [3] | Zhang, Y. (Zhang, Y..) [4] | Tu, Y. (Tu, Y..) [5] | Zhang, Y. (Zhang, Y..) [6] (Scholars:张云霄) | Huang, M. (Huang, M..) [7]

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Abstract:

The content of acetylene is one of the important indicators of transformer fault diagnosis. Due to the differences between individual transformers, the content of acetylene gas varies greatly. The adoption of a single threshold is likely to lead to false alarm or missing report of the diagnosis results. The difference of gas threshold in oil has been paid more and more attention, but the difference characteristics of acetylene gas threshold in oil and its influencing factors are still unclear. This paper uses 10 kV test transformer and fault chamber to build a simulation test platform for gas production and diffusion under pin plate and column plate faults. The acetylene content in different stages of fault development was measured, and the gas distribution model was statistically analyzed. On this basis, based on the P-R curve, the attention value and warning value of acetylene content during the development of two kinds of faults are calculated, and the difference of threshold values of different oilpaper materials is compared. The results show that there are obvious differences in acetylene thresholds under different oil paper materials and faults, and the sensitivity and accuracy of fault diagnosis based on oil chromatography can be improved by using the calculated differential threshold.  © 2023 IEEE.

Keyword:

acetylene differentiated threshold value discharge fault transformer Weibull distribution

Community:

  • [ 1 ] [Liu R.]Hubei Electric Power Research Institute, State Grid Corporation of China, Wuhan, China
  • [ 2 ] [Yang T.]Hubei Electric Power Research Institute, State Grid Corporation of China, Wuhan, China
  • [ 3 ] [He Q.]Hubei Electric Power Research Institute, State Grid Corporation of China, Wuhan, China
  • [ 4 ] [Zhang Y.]Hubei Electric Power Research Institute, State Grid Corporation of China, Wuhan, China
  • [ 5 ] [Tu Y.]Hubei Electric Power Research Institute, State Grid Corporation of China, Wuhan, China
  • [ 6 ] [Zhang Y.]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 7 ] [Huang M.]North China Electric Power University, School of Electrical and Electronic Engineering, Beijing, China

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Year: 2023

Page: 674-677

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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