Journal of the Korean Institute of Illuminating and Electrical Installation Engineers (조명전기설비학회논문지)

The Korean Institute of IIIuminating and Electrical Installation Engineers (한국조명전기설비학회)
권호 표지
DOI QR코드

DOI QR Code

Implementation of on Expert System to Supervise GIS Arrester Facilities

GIS 피뢰설비 관리를 위한 전문가 시스템 구현

  • 길경석 (한국해양대학교 전기전자공학부) ;
  • 송재용 (한국해양대학교 산업기술연구소) ;
  • 김일권 (한국해양대학교 대학원 전기공학과) ;
  • 문승보 (한국해양대학교 대학원) ;
  • 권장우 (동명대학교 컴퓨터공학과)
  • Published : 2007.01.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper dealt with the design and implementation of an expert system to monitor and diagnose the lightning arresters in GIS substations. The expert system consists of a data acquisition module(DAM) based on microprocessor and diagnostic algorithms. The DAM measures and analyzes several parameters necessary for the arrester diagnosis such as system voltages, leakage current components, and temperatures. Also, it includes an intelligent surge counter which can record the date and tin, the polarity, and the amplitude of surge currents. All the data acquired is transmitted to a remote computer by a low rate wireless network specified in IEEE 802.15.4 to avoid electromagnetic intereference under high voltage and large current environments. The decision-making for the arrester diagnosis completes with a Java Expert System Shell(JESS) which is composed of a knowledge base, an inference engine and a graphic user interface(GUI).

본 논문은 가스절연변전소에 설치되어 있는 피뢰설비의 감시와 진단이 가능한 전문가 시스템의 선계 및 구현에 대하여 기술하였다. 제안한 전문가 시스템은 마이크로프로세서 기반의 데이터 취득 모듈과 진단 알고리즘으로 구성되며, 피뢰기 진단에 필요한 계통전압, 누설전류성분 및 온도 등을 검출하고 분석한다. 또한 서지전류의 발생시각, 극성 및 크기를 기록할 수 있는 지능형 서지 카운터를 내장하고 있다. 측정된 모든 데이터는 IEEE 802.15.4에 규정된 저속 무선망을 통해 원격지의 컴퓨터로 전송되며, 이로 인해 고전압 대전류 환경에서도 전자계 간섭을 피할 수 있다. 전문가 시스템에서 피뢰기의 진단은 지식 베이스와 추론 엔진, 그리고 그래픽 사용자 인터페이스로 구성된 JESS(Java Expert System Shell)를 이용하여 결정한다.

Keywords

References

  1. M. Bartkowiak et al., 'Failure Modes and Energy Absorption Capability of ZnO Varistors', IEEE Trans. Power Delivery, Vol. 14, No. 1, pp. 152-162, 1999 https://doi.org/10.1109/61.736708
  2. O. Nigol, 'Methods for Analyzing the Performance of Gapless Metal Oxide Surge Arresters', IEEE Trans. Power Delivery, Vol. 7, No. 3, pp. 1256-1262, 1992 https://doi.org/10.1109/61.141839
  3. J. B. KIM et al., 'Development of Monitoring and Diagnostic System for SF6 Gas Insulated Switchgear', Conference Record of the 2002 IEEE International Symposium on Electrical Insulation, pp. 453-456, 2002
  4. S.Shirakawa et al., 'Maintenance of surge arrester by a portable arrester leakage current detector', IEEE Trans. Power Delivery, Vol. 3, No. 3, pp. 998-1003, 1988 https://doi.org/10.1109/61.193879
  5. J. Lundquist et al., 'New method for measurement of the resistive leakage currents of metal-oxide surge arrester in service', IEEE Trans. Power Delivery, Vol. 5, No. 4, pp. 1811-1822, 1990 https://doi.org/10.1109/61.103677
  6. Gyung-Suk Kil et al., 'Measurement Method of the Resistive Leakage Current for Lightning Arrester Diagnosis', KIEEME Trans. Electrical and Electronic Materials, Vol. 6, No. 2, pp. 63-66, 2005 https://doi.org/10.4313/TEEM.2005.6.2.063
  7. IEC 60099-5, Surge arresters- Part 5 : Selection and application recommendations, International Electrotechnical Commission, 2001
  8. National Instrument Co., LabView Ver. 8.0, National Instrument Co., 2005
  9. Il-Kwon Kim et al., 'A Study on the Influence of Harmonics in Power System Voltage on Arrester Diagnostics and its Compensation', KIEE Trans. Electrophysics and Application, Vol. 54-C, No. 11, pp.493-497, 2005
  10. Jinbo Kuang et al., 'Temperature Distribution in a ZnO Arrester Subjected to Multiple Current Impulses', Proceeding of the 1996 International Symposium on Electrical Insulation, pp. 494-497, 1996
  11. Y. Zhang et. al., 'An Artificial Neural Network Approach to Transformer Fault Diagnosis', IEEE Trans. Power Delivery, Vol. 11, No. 4, pp. 1836-1841, 1996 https://doi.org/10.1109/61.544265
  12. In-Hyuk Choi et al., 'Development of Diagnostic Algorithm and Expert System to diagnose Power Transformers by the methods of Gas Analysis', Journal of KIIEE, Vol. 15, No. 5, pp. 68-74, 2001

Cited by

  1. An Experience-Type Car Maintenance Training System based on Logic Simulation vol.23, pp.2, 2014, https://doi.org/10.9709/JKSS.2014.23.2.073