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Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

Author

Listed:
  • Dmitry A. Ivanov

    (Institute of Electric Power Engineering and Electronics, Kazan State Power Engineering University, 420066 Kazan, Russia)

  • Marat F. Sadykov

    (Institute of Electric Power Engineering and Electronics, Kazan State Power Engineering University, 420066 Kazan, Russia)

  • Danil A. Yaroslavsky

    (Institute of Electric Power Engineering and Electronics, Kazan State Power Engineering University, 420066 Kazan, Russia)

  • Aleksandr V. Golenishchev-Kutuzov

    (Institute of Electric Power Engineering and Electronics, Kazan State Power Engineering University, 420066 Kazan, Russia)

  • Tatyana G. Galieva

    (Institute of Electric Power Engineering and Electronics, Kazan State Power Engineering University, 420066 Kazan, Russia)

Abstract

The article describes a complex of non-contact methods for remote diagnosis of high-voltage insulators as well as the two-channel method for remote diagnostics of the operating state of high-voltage insulators, based on the registration of partial discharges by electromagnetic and acoustic sensors. The presented device allows visual inspection and searches for faulty high-voltage equipment and a remote non-contact method of recording high-intensity electric fields of industrial frequency and their spatial distribution based on the electro-optical effect. The scheme of using the system for monitoring and diagnosing the technical condition of high-voltage support insulators of open switchgear is described. The results of experimental studies confirm the possibility of industrial applicability of the proposed method for non-contact remote diagnostics of the state of high-voltage insulators under operating voltage.

Suggested Citation

  • Dmitry A. Ivanov & Marat F. Sadykov & Danil A. Yaroslavsky & Aleksandr V. Golenishchev-Kutuzov & Tatyana G. Galieva, 2021. "Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation," Energies, MDPI, vol. 14(18), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5670-:d:632132
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    References listed on IDEAS

    as
    1. Wojciech Sikorski & Krzysztof Walczak & Wieslaw Gil & Cyprian Szymczak, 2020. "On-Line Partial Discharge Monitoring System for Power Transformers Based on the Simultaneous Detection of High Frequency, Ultra-High Frequency, and Acoustic Emission Signals," Energies, MDPI, vol. 13(12), pages 1-37, June.
    2. Yuanlin Luo & Zhaohui Li & Hong Wang, 2017. "A Review of Online Partial Discharge Measurement of Large Generators," Energies, MDPI, vol. 10(11), pages 1-32, October.
    3. Shuguo Gao & Ying Zhang & Qing Xie & Yuqiang Kan & Si Li & Dan Liu & Fangcheng Lü, 2017. "Research on Partial Discharge Source Localization Based on an Ultrasonic Array and a Step-by-Step Over-Complete Dictionary," Energies, MDPI, vol. 10(5), pages 1-12, April.
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