46 / 2022-03-06 18:28:08
Research on aging diagnosis of oil-paper insulation based on Raman spectroscopy with extended data
oil-paper insulation,Raman spectroscopy,aging diagnosis,extended data,Elman nerual network,SVM (support vector machine)
终稿
Zhuang Yang / Chongqing University
Jinchao Du / China Electric Power Research Insititute
Weigen Chen / Chongqing University;State Key Laboratory of Power Transmission Equipment &System Security and New Technology
Zhixian Yin / Chongqing University
Dingkun Yang / Chongqing University of Posts And Telecommunications
The aging state of the oil-paper insulation system inside the transformer is an important factor affecting the safe operation of the transformer. Considering that oil-paper insulation samples are difficult to obtain in large quantities, this paper first prepares oil-paper insulation samples by accelerated thermal aging test and then tested by Raman spectroscopy. Elman neural network is then used to simulate the real spectrum of the sample to obtain a large number of simulated spectra. Finally, all the Raman spectra obtained were used to build a diagnostic model for the aging of oil-paper insulation. The results show that the obtained simulation spectra are valid and the oil-paper insulation aging diagnosis model established in this paper can effectively evaluate the aging state of transformers. This paper develops a new way to solve small samples in oil-paper insulation diagnostic model, and at the same time lays the foundation for further quantitative assessment of the aging state of transformers.
重要日期
  • 会议日期

    09月25日

    2022

    09月29日

    2022

  • 08月15日 2022

    提前注册日期

  • 09月10日 2022

    报告提交截止日期

  • 11月10日 2022

    注册截止日期

  • 11月30日 2022

    初稿截稿日期

  • 11月30日 2022

    终稿截稿日期

主办单位
IEEE DEIS
承办单位
Chongqing University
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