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1 2016 년도한국철도학회추계학술대회논문집 KSR2016A257 TEV센서를이용한저압배전반에서직렬아크신호의검출 Detection of Series Arc Signals by TEV Sensor in Low-voltage Switchboard 박서준 *, 황성철 *, 왕국명 *, 길경석 * Seo-Jun Park *, Seong-Cheol Hwang *, Guoming Wang *, Gyung-Suk Kil * Abstract This paper presents the detection of series arc signals by a transient earth voltage (TEV) sensor in low-voltage switchboard to avoid the electrical fires. A cord-cord and a terminal block-y terminal were used to simulate typical arc sources in the switchboard. The arc signals were detected using a TEV sensor with a frequency range up to 100 MHz and were acquired by a data acquisition unit. It was revealed that the TEV signal was detected simultaneously with the shoulder of arc current. In addition, the two types of arc faults were detected in the frequency range of MHz, whereas the peak spectrum of the cord-cord was distributed in MHz and that of the terminal block-y terminal was in MHz. Keywords : Series arc, Switchboard, TEV sensor, Frequency 초록본논문은저압배전반에서발생되는전기화재를예방하기위하여 TEV(Transient Earth Voltage) 센서를이용한직렬아크검출에관해기술하였다. 직렬아크를생성하기위해전선간및터미널블록접속부 2 종의결함을제작하였다. 100 MHz 까지의주파수성분을검출할수있는 TEV 센서를이용해아크신호를측정하여데이터수집모듈로신호를수집하고이를분석하였다. 그결과직렬아크의전류파형에서관측되는영점지연 (Shoulder) 구간에 TEV 신호가검출됨을확인하였다. 또한 2 종의결함에서발생된 TEV 신호를이용해주파수영역에서비교한결과, 모든결함이 MHz 에서동일하게분포하였다. 반면에 Peak Spectrum 분석결과전선간의결함에서는 MHz 로, 터미널블록접속부에서는 MHz 로상이한특성을보였다. 주요어 : 직렬아크, 배전반, TEV 센서, 주파수 1. 서론 산업 경제의성장으로전기수요량이급증함에따라전기화재로인한사고도증가하고있다. 2015년국민안전처의원인별화재사고통계치에따르면총 44,435건중전기로인한화재사고는 8,989건으로 23% 이상을차지하였다. 특히아크발생으로인한단락과누전사고는전기화재발생원인에서 60% 이상의높은비율을보였다 [1]. 이와같이폐쇄적인공간에서운행하는철도차량의저압배전반에서도아크로인한전기화재가발생될수있으며, 인적 물적손실에대한파급효과도대규모로확대될수있다 [2-4]. 교신저자 : 한국해양대학교공과대학전자전기정보공학부 (kilgs@kmou.ac.kr) * 한국해양대학교공과대학전기전자공학과
2 아크는전기기기의접촉불량및절연파괴에기인하며, 장기간경과시국부적인과열및단락으로발전되어전기화재로이어진다 [5]. 현재차단기및퓨즈등의보호기기를통해전기화재를예방하고있지만, 사고발생직후작동되기때문에사전에예측이불가능하다. 따라서조기에아크신호를검출하여위험신호를확인할수있는진단기술이필요하다 [6]. 본논문에서는 TEV(Transient Earth Voltage) 센서를이용하여직렬아크발생시방사되는전자기파를통해신호를검출하였다. 또한저압배전반에서발생가능한대표적인 2종의결함을모의하여특성을비교하였다. 2. 본론 2.1 실험계의구성저압배전반의전선및터미널접속부불량에의해발생되는직렬아크방전을모의하기위하여 Fig. 1과같이실험계를구성하였다. UL 1699의규정에따른아크발생장치를제작하였으며, 부하저항기를조절하여 5A의전류를통전시켰다. 아크발생지점에서 1m 이격시킨금속플레이트에 TEV센서를부착하여아크로부터방사되는전자기파를검출하였다. 또한아크의전류파형과비교하기위하여부하측에 HFCT를설치하였다. 아크신호는오실로스코프 (5 GS/s) 로측정하였으며, DAQ(Data Acquisition) 를통해수집하였다. Fig. 2와같이일반적으로저압배전반에서발생될수있는전선간및터미널블록접속부 2 종의결함을제작하여실험을수행하였다. Fig. 1 Experimental setup (a) Cord-cord Fig. 2 Arc sources (b) Terminal block-y terminal
3 2.2 결과및분석일반적으로직렬아크의전류파형은방전의개시및소멸로인하여영점부근에서약 μs의영점지연 (Shoulder) 현상이발생한다 [7,8]. Fig. 3은아크발생에의한전류 ( 노란색 ) 및 TEV 신호 ( 파란색 ) 파형이다. HFCT를통해전류파형을측정한결과 0-40 ms 구간에서영점지연현상이나타남을알수있다. 동일한조건에서 TEV센서를이용해아크에의한전자기파를검출한결과, 영점지연현상이나타난구간에서 TEV 신호가측정되었다. 따라서 TEV센서를통해충분히아크검출이가능함을확인하였다. Fig. 3 Current and TEV signal of arc fault 시간영역에서는결함에따른아크신호의특성을판단하기어렵기때문에 FFT(Fast Fourier Transform) 를이용해주파수영역에서분석하였다. Fig. 4는전선간의결함에서발생되는 TEV 신호의시간및주파수영역을나타내었다. 주파수영역의그래프는 log-scale 및상대크기로표현하였다. 분석결과주파수 MHz 영역에서분포하였으며, 3.96 MHz에서가장높은신호크기를보였다. Peak spectrum으로분석하였을때 MHz에서분포하는특성을보였다. (a) Time domain Fig. 4 TEV signal of cord-cord (b) Frequency domain
4 Fig. 5는터미널블록접속부에서발생되는 TEV 신호의시간및주파수영역에대한결과이다. 분석결과전선간결함과동일하게주파수 MHz영역에서분포하였고, 0.87 MHz에서가장높은신호크기를보였다. Peak spectrum의경우 MHz에서분포하는특성을보였다. (a) Time domain (b) Frequency domain Fig. 5 TEV signal of terminal block-y terminal Table 1은전선간및터미널블록접속부 2종의결함에대한 TEV 신호의주파수성분을비 교한것이다. 결함모두 MHz영역에서동일하게분포하는특성을보였다. 반면에 Peak spectrum 분석결과, 전선간의결함은 MHz이며, 터미널블록접속부결함의경우 MHz로상이한특성을보였다. Table 1 Frequency range of TEV signal Arc fault Frequency range (MHz) Full Peak spectrum Cord-cord Terminal block-y terminal 결론본논문에서는저압배전반에서발생할수있는전기화재를예방하기위해 TEV 센서를이용해직렬아크를검출하고, 제작된결함계를통해 TEV 신호를분석및비교하였다. 직렬아크의전류파형에나타나는영점지연구간에서 TEV 신호가측정되었으며, 이로인해아크발생유무를충분히판단할수있었다. 또한전선간및터미널블록접속부 2종의결함에대해 TEV 신호를분석한결과, 2종모두주파수 MHz 구간에서분포하였다. 반면에 Peak spectrum으로분석한결과전선간의경우 MHz에서, 터미널블록접속부의경우 MHz로상이한특성을보였다.
5 후기 본연구는 2015 년도미래창조과학부의재원으로연구개발특구진흥재단의지원을받아수행한연구과제입니다. (2015BSI1051) 참고문헌 [1] Ministry of Public Safety and Security (2015) Fire statistical yearbook. [2] H.K. Ji, C.Y. Park, G.S. Kil, I.K. Kim, et al. (2008) Detection of series arc signal in low-voltage systems, Spring Conference of the Korean Society for Railway, pp [3] G.S. Kil, H.K. Ji, D.W. Park, I.K. Kim, et al. (2008) Detection method of series arc signal, Journal of the Korean Society for Railway, 11(5), pp [4] W.S. Kwon, S.K. Choi, S.B. Bang, C.M. Kim, et al. (2009) Series arc wave analysis and detection algorithm, Autumn Conference of the Korean institute of Power Electronics, pp [5] G.D. Gregory, G.W. Scott (1988) The arc-fault circuit interrupter, an emerging, IEEE Transactions on Industry Applications, 34(5), pp [6] C.E. Restrepo (2007) Arc fault detection and discrimination methods, Proceedings of the 53rd IEEE Holm Conference on Electrical Contacts, pp [7] G.D. Gregory, K. Wong, R.F. Dvorak (2004) More about arc-fault circuit interrupters, IEEE Transactions on Industry Application, 40(4), pp [8] D.W. Park, I.K. Kim, S.Y. Choi, G.S. Kil (2008) Detection algorithm of series arc for electrical fire prediction, International Conference on Condition Monitoring and Diagnosis, pp
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