Transformer Winding Deformation Detection and Fault Identification Based on Distributed Optical Fiber Sensing
编号:270 访问权限:仅限参会人 更新:2020-11-11 12:10:19 浏览:88次 张贴报告

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摘要
The traditional detecting methods of winding deformation are off-line detection, and can not identify the winding deformation mode. This paper proposed a new transformer winding deformation detection method based on distributed optical fiber sensing. A fiber-optical composite winding model was designed, the influence of optical fiber on the electric field in oil was simulated, and a transformer winding model with built-in optical fiber was developed. The typical deformations of the transformer were set, using Brillouin optical time domain reflectometry (BOTDR) to measure the strain change of the fiber. Finally, the detection signal was pattern-recognized by the extreme learning machine (ELM). According to the results, the accuracy of ELM was more than 94% for different deformation forms. The distributed optical fiber sensing technology can detect the transformer winding deformation effectively, which provides a new approach for on-line monitoring of transformer winding deformation.
关键词
Brillouin optical time domain reflectometer,distributed optical fiber,extreme learning machine,online monitoring,transformer winding deformation
报告人
Junyi Yin
North China Electric Power University

稿件作者
Junyi Yin North China Electric Power University
Yunpeng Liu North China Electric Power University
Naihao Shi the George Washington University
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重要日期
  • 会议日期

    10月21日

    2019

    10月24日

    2019

  • 10月13日 2019

    摘要录用通知日期

  • 10月13日 2019

    初稿截稿日期

  • 10月14日 2019

    初稿录用通知日期

  • 10月24日 2019

    注册截止日期

  • 10月29日 2019

    终稿截稿日期

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