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Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation

Author

Listed:
  • Shuguo Gao

    (State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, China)

  • Chao Xing

    (State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, China)

  • Zhigang Zhang

    (State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, China)

  • Chenmeng Xiang

    (State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, China)

  • Haoyu Liu

    (State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, China)

  • Hongliang Liu

    (State Grid Hebei Electric Power Co., Ltd., Electric Power Research Institute, Shijiazhuang 310014, China)

  • Rongbin Shi

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Sihan Wang

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Guoming Ma

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

Abstract

Traditional high-voltage reactor monitoring and diagnosis research has problems such as high sampling demand, difficulty in noise reduction on site, many false alarms, and lack of on-site data. In order to solve the above problems, this paper proposes an acoustic–electric fusion high-voltage reactor acquisition system and defect diagnosis method based on reactor pulse current and ultrasonic detection signal. Using the envelope peak signal as the basic detection data, the sampling requirement of the system is reduced. To fill the missing data with partial discharge (PD) information, a method based on k-nearest neighbor (KNN) is proposed. An adaptive noise reduction method is carried out, and a noise threshold calculation method is given for the field sensors. A joint analysis method of acoustic and electrical signals based on correlation significance is established to determine whether a discharge event has occurred based on correlation significance. Finally, the method is applied to a UHV reactor on the spot, which proves the effectiveness of the method proposed in this paper.

Suggested Citation

  • Shuguo Gao & Chao Xing & Zhigang Zhang & Chenmeng Xiang & Haoyu Liu & Hongliang Liu & Rongbin Shi & Sihan Wang & Guoming Ma, 2022. "Early Warning of High-Voltage Reactor Defects Based on Acoustic–Electric Correlation," Energies, MDPI, vol. 15(19), pages 1-11, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7196-:d:929998
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    References listed on IDEAS

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    1. Saleh Alsuhaibani & Yasin Khan & Abderrahmane Beroual & Nazar Hussain Malik, 2016. "A Review of Frequency Response Analysis Methods for Power Transformer Diagnostics," Energies, MDPI, vol. 9(11), pages 1-17, October.
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