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Frequency Spectrum Analysis of Corona Discharge Source Measured by Ultrasound Detector

초음파 감지기로 측정한 코로나 방전 소스의 주파수 스펙트럼 분석

  • Cho, Hyun-Seob (Department of Electronic Engineering, ChungWoon University)
  • Received : 2019.02.11
  • Accepted : 2019.02.14
  • Published : 2019.02.28

Abstract

This paper addressed the spectrum of ultrasonic waves produced by arc and/or coronal discharge inside the switchboard. Portable ultrasound sensors are useful for detecting discharge phenomena, such as coronal means in electrical systems. However, a typical handheld ultrasound detector has a disadvantage of determining the type of problem by listening to the sound characteristics and predicting the results, as a result of the determination of whether a discharge is present. Therefore, a new method of analysis is required to distinguish ultrasonic characteristics. In this paper, we published an ultrasound analysis case study to visualize the sound of ultrasonic waves measured with ultrasonic sensors. From the results of the experiment, it was possible to detect coronal discharge and serial arc discharge without interference by the ultrasonic detection system.

본 논문에서는 수배전반 내 코로나 및 직렬아크 발생 시 나타나는 초음파 신호의 측정 및 분석에 대해 기술하였다. 휴대용 초음파 감지기는 전기 시스템에서 발생하는 코로나와 같은 방전 현상 감지에 유용하다. 그러나 일반적인 휴대용 초음파 감지기는 방전 여부에 대한 판단 결과가 사용자의 주관적 반응에 영향을 미치며, 음향 특성을 듣고 결과를 예측함으로써 문제 유형을 판별하는 것이 어렵다는 단점을 가지고 있다. 따라서 초음파 특성을 구별하는 새로운 분석 방법이 필요하다. 본 논문에서는 초음파 감지기로 측정 한 초음파 음향을 시각화하기 위한 초음파 분석 사례를 연구하였다. 실험 결과 초음파탐지계통은 외부소음의 영향을 받지 않고 배전반에서 코로나 및 직렬 아크 방전을 검출할 수 있었다.

Keywords

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Fig. 1. Configuration of the experimental set-up

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Fig. 2. The developed program

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Fig. 3. View of the corona sound as seen in the frequency-domain analysis. Ultrasonic signal [100 mV/div, 10 ms/div]

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Fig. 4. View of the corona sound as seen in the time-domain analysis. Frequency spectrum [2.0 mV/div, 10 kHz/div]

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Fig. 5. View of the arching sound as seen in frequency-domain analysis in the scanned CT. Frequency spectrum [2.0 mV/div, 10 kHz/div]

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Fig. 6. View of the arching sound as seen in the time-domain analysis in the scanned CT. Current signal [2.0 V/div, 10 ms/div]

References

  1. S. Tenbohlen, D. Uhde, and J. Poittevin (2000) Enhanced Diagnosis of Power Transformers using On- and Off-line Methods: Results, Examples and Future Trends, CIGRE Paris, No. 12-204.
  2. National Emergency Management Agency (2010) A Statistical Analysis on the Electric Accident.
  3. Wen-Jun Li, Yuan-Chun Li (2005) Arc Fault Detection Based on Wavelet Packet, Proc. of 2005 4th International Conference on Machine Learning and Cybernetics, Vol. 3, pp.1783-1788.
  4. Gyung-Suk Kil, Hong-Keun Ji, Dae-Won Park, Il-Kwon Kim, et
  5. Mark Goodman, Using Sound Imaging to Enhance Your Diagnosis, UE Systems (2011)
  6. James Brady, Corona and Tracking Conditions in Metal-clad Switchgear Case Studies, Brady Infrared Inspections (2006)
  7. Mark Goodman, Methods of Inspection to Determine the Presence of Potential Arc-Flash Incidents, NETA WORLD ( 2007).
  8. C. Li, F. Dawson, H. Kojori, C. Meyers, et al. (2003) SAE Technical Papers 2003-01-3037, 591.