한국화재소방학회논문지 (Fire Science and Engineering)

  • 제29권2호
  • /
  • Pages.1-7
  • /
  • 2015
  • /
  • 2765-060X(pISSN)
  • /
  • 2765-088X(eISSN)
한국화재소방학회 (Korean Institute of Fire Science and Engineering)
권호 표지
DOI QR코드

DOI QR Code

트래킹에 의한 전기화재 가능성 예측

Prediction for Possibility of the Electric Fire by Tracking Breakdown

  • 투고 : 2014.09.15
  • 심사 : 2015.04.28
  • 발행 : 2015.04.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

전기화재의 주요 원인 중 하나인 트래킹은 서서히 진전하는 특징을 가지기 때문에 진전단계를 분석함으로서 화재가능성을 예측할 수 있다. 본 논문은 부하가 연결된 모의 전기설비에서 트래킹에 의한 전기화재 가능성을 예측하고자 시도하였다. 부하는 무유도 저항을 사용하였고, 트래킹은 모의 전기설비의 일부인 비닐캡타이어 타원형코드에 전해액을 적하하여 발생시켰다. 트래킹에 의한 전기화재 가능성을 예측하기 위해 모의 전기설비의 전체 전류파형을 검출하였다. 전류파형으로부터 트래킹 진전을 분석하기 위해 시간-에너지 변환과 확률분포를 이용하였고, 이를 신경망에 입력함으로써 전기설비 내에서 전기화재의 발생가능성을 4단계로 예측할 수 있게 하였다.

Tracking, which is one of main reasons of the electric fire, progresses gradually, and therefore, the possibility of fire caused by tracking can be predicted by analyzing the stage of its progress. This paper is conducted in order to predict possibility of the electric fire caused by the tracking in the simulated electric equipment with load. Non-inductive resistance is used as the load. The tracking is happened in a Polyvinyl-chloride-sheathed flat cord, which is a part of the simulated electric equipment by means of dropping of electrolyte droplet. In order to predict the possibility of electric fire caused by tracking, we detect the whole current waveforms of the simulated electric equipment. The time-energy analysis and probability distribution are used for analysis of the tracking progress from the whole current waveforms. In accordance with the results is used for input date of Neural networks, the neural networks can be predict possibility of the electric fire in the electric equipment by 4 stages.

키워드

참고문헌

  1. Korea Electrical Safety Corporation, "A Study on Hazard of Electrical Fire by Carbonization and Heating for a Wiring Apparatus" (1996).
  2. S. W. Jee, K. G. Ok, S. K. Kim and C. H. Lee, "Detection of Indication of Electric Accident in Simulated Electric Equipments Using Standard Deviation and Probability Distribution", Journal of Korean Institute of Fire Science & Engineering, Vol. 23, No. 3, pp. 11-16 (2009).
  3. T. Tanaka, K. Noto and J. Kitagawa, "A Basic Study on Outdoor Insulators of Organic Materials", IEEE Transactions on Electrical Insulation, Vol. EI-13, No. 3, pp. 184- 193, (1978). https://doi.org/10.1109/TEI.1978.298128
  4. N. Yoshimura, M. Nishida and F. Noto, "Influence of the Electrolyte on Tracking Breakdown of Organic Insulating Materials", IEEE Transactions on Electrical Insulation, Vol. EI-16, No. 6, pp. 510-520 (1981). https://doi.org/10.1109/TEI.1981.298382
  5. F. Noto and K. Kawamura, "Tracking and Ignition Phenomena of Polyvinyl Chloride Resin under Wet Polluted Conditions", IEEE Transactions on Electrical Insulation, Vol. EI-13, No. 6, pp. 418-425 (1978). https://doi.org/10.1109/TEI.1978.298088
  6. S. W. Jee, C. H. Lee and K. S. Lee, "Classification of Bridge Current and Analysis of Heat Transfer Characteristics in Polyvinyl-Chloride-Sheathed Flat Cord Under Tracking", Journal of Electrical Engineering & Technology, Vol. 8, No. 1, pp. 176-182 (2013). https://doi.org/10.5370/JEET.2013.8.1.176
  7. N. Yoshimura, M. Nishida and F. Noto, "Light Emission from Tracking Discharges on Organic Insulation", IEEE Transactions on Electrical Insulation, Vol. EI-19, No. 2, pp. 149-155 (1984). https://doi.org/10.1109/TEI.1984.298787
  8. M. Nishida, N. Yoshimura and F. Noto, "Light Sensors as Detectors of Tracking Deterioration", IEEE Transactions on Electrical Insulation, Vol. EI-22, No. 4, pp. 509- 516 (1987). https://doi.org/10.1109/TEI.1987.298917
  9. S. Kumagai and N. Yoshimura, "Impacts of Thermal Aging and Water Absorption on the Surface Electrical and Chemical Properties of Cycloaliphatic Epoxy Resin", IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 7, No. 3, pp. 424-431 (2000). https://doi.org/10.1109/94.848931
  10. M. Nishida, N. Yoshimura, F. Noto and M. S. A. A. Hammam, "Detection of Tracking Carbon Path Using Visual and Thermal Images", IEEE Transactions on Electrical Insulation, Vol. 27, pp. 1050-1053 (1992). https://doi.org/10.1109/14.256480
  11. S. W. Jee, C. H. Lee and K. S. Lee, "Signal Analysis Methods to Distinguish Tracking Process Using Timefrequency Analysis", IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 16, No. 1, pp. 99-106 (2009). https://doi.org/10.1109/TDEI.2009.4784556