Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1997.07c
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- Pages.924-926
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- 1997
A Study on the Detection of LIF and HIF Using Neural Network
신경회로망을 이용한 LIF 및 HIF검출에 판한 연구
- Choi, H.S. (Key-in system) ;
- Park, S.W. (Sung Kyun Kwan University) ;
- Chae, J.B. (Sung Kyun Kwan University) ;
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Kim, C.H.
(Sung Kyun Kwan University)
- 최해술 (기인시스템) ;
- 박성원 (성균관대학교 전기.전자 및 컴퓨터 공학부) ;
- 채종병 (성균관대학교 전기.전자 및 컴퓨터 공학부) ;
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김철환
(성균관대학교 전기.전자 및 컴퓨터 공학부)
- Published : 1997.07.21
Abstract
A high impedance fault(HIF) in a power system could be due to a downed conductor, and is a dangerous situation because the current may be too small to be detected by conventional means. In this paper, HIF(High impedance fault) and LIF(Low impedance fault) detection methods were reviewed. No single defection method can detect all electrical conditions resulting from downed conductor faults, because high impedance fault have arc phenomena, asymmetry and randomness. Neural network are well-suited for solving difficult signal processing and pattern recognition problem. This paper presents the application of artificial neural network(ANN) to detect the HIF and LIF. Test results show that the neural network was able to identify the high impedance fault by real-time operation. Furthermore, neural network was able to discriminate the HIF from the LIF.
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