본문 바로가기
HOME> 논문 > 논문 검색상세

논문 상세정보

Power Transformer Diagnosis Using a Modified Self Organizing Map

Lee J. P.    (Dept. of Electrical Engineering, Chungbuk National University   ); Ji P. S.    (Dept. of Electrical Engineering, Chungju National University   ); Lim J. Y.    (Dept. of Electrical Engineering, Daeduk College   ); Kim S. S.    (Dept. of Electrical Engineering, Chungbuk National University  );
  • 초록

    Substation facilities have become extremely large and complex parts of electric power systems. The development of condition monitoring and diagnosis techniques has been a very significant factor in the improvement of substation transformer security. This paper presents a method to analyze the cause, the degree, and the aging process power transformers by the Self Organizing Map (SOM) method. Dissolved gas data were non-linearly transformed by the sigmoid function in SOM that works much the same way as the human decision making process. The potential for failure and the degree of aging of normal transformers are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.


  • 주제어

    Aging .   ANN .   DGA .   Diagnosis .   SOM.  

  • 참고문헌 (16)

    1. Y Kashima, 'Automatic Field Monitoring of Dissolved Gases in Transformer Oil', IEEE Trans., Vol. PAS-100, pp. 1538-1544, 1981 
    2. H. Tsukioka, K. Sugawara, E. Mori, S. Hukumori and S. Sakai, 'New Apparatus for Detecting H2, CO and CH4 Dissolved in Transformer Oil', IEEE Transaction on Electrical Insulation, Vol. EI-13, No. 4, pp. 409-419, 1983 
    3. Hong Tzer Yang, Yann Chang Huang, 'Intelligent Decision Support for Diagnosis of Incipient Transformer Faults Using Self-Organizing Polynomial Networks', IEEE Transaction on Power Systems, Vol. 13, No. 3, pp. 946-952, August. 1998 
    4. LiMin Fu, Neural Network in computer Intelligence, McGraw-Hill, pp. 48-55, 1994 
    5. R. R. Rogers, 'IEEE and IEC Code To Interpret Incipient Faults in Transformers Using Gas in Oil Analysis', IEEE Transaction on Electrical Insulation, Vol. EI-13, No. 5, pp. 349-354, 1978 
    6. H. Yoshida, Y. Ishioka, T. Suzuki, T. Yanari and T. Teranishi, 'Degradation of Insulating Materials of Transformers', IEEE Transaction on Electrical Insulation, Vol. EI-22, No. 6, pp. 795-800, 1987 
    7. Philip D. Wasserman, Neural Computer Theory and Practice, Van. Mostrand Reinold, pp. 64-70, 1989 
    8. W. Xu, D. Wang, Z. Zhou, H. Chen, 'Fault Diagnosis of Power Transformers: Application of Fuzzy Set Theory, Expert Systems and Artificial Neural Networks', IEE Proc.-Sci Meas. Technol., Vol. 144, No. 1, pp. 39-44, January. 1997 
    9. J.P. Lee, P.S. Ji, S.C. Nam, J.Y. Lim, 'Aging Characteristics of Power Transformer Oil and Development of It's Analysis Using KSOM', in Proceedings of ICEE 98, Vol. II, Kyongju, Korea, pp. 461-464, July. 1998 
    10. H. Tsukioka, K. Sugawara, E. Mori and H. Yamaguchi, 'New Apparatus For Detecting Transformer Faults', IEEE Transaction on Electrical Insulation, Vol. EI-21, No. 2, pp. 221-229, 1986 
    11. C. E. Lin, J. M. Ling, C. L. Huang, 'An Expert System for Transformer Fault Diagnosis Using Dissolved Gas Analysis', IEEE Transaction on Power Delivery, Vol. 8, No. 1, pp. 231-238, January 1993 
    12. M. Duval, 'Dissolved Gas Analysis: It Can Save Your Transformer', IEEE Electrical Insulation Magazine, Vol. 5, No. 6, pp. 22-26, 1989 
    13. Y. Kamata, 'Diagnostic Methods for Power Transformer Insulation', IEEE Transaction on Electrical Insulation, Vol. EI-21, No. 6, pp. 1045-1048, 1986 
    14. Zhenyuan Wang, Yilu Liu, P.J. Griffin, 'A Combined ANN and Expert System Tool for Transformer Fault Diagnosis', IEEE Transaction on Power Delivery, Vol. 13, No. 4, pp. 1224-1229, October. 1998 
    15. Y. C. Huang, H. T. Yang, C. L. Huang, 'Developing a New Transformer Fault Diagnosis System Through Evolutionary Fuzzy Logic', IEEE Transaction on Power Delivery, Vol. 12, No. 2 pp. 761-767, April. 1997 
    16. Y. Zhang, X. Ding, Y. Liu, P.J. Griffin, 'An Artificial Neural Network Approach to Transformer Fault Diagnosis', IEEE Transaction on Power Delivery, Vol. 11, No. 4, pp. 1836-1842, October. 1996 

 활용도 분석

  • 상세보기

    amChart 영역
  • 원문보기

    amChart 영역

원문보기

무료다운로드
  • NDSL :
유료다운로드

유료 다운로드의 경우 해당 사이트의 정책에 따라 신규 회원가입, 로그인, 유료 구매 등이 필요할 수 있습니다. 해당 사이트에서 발생하는 귀하의 모든 정보활동은 NDSL의 서비스 정책과 무관합니다.

원문복사신청을 하시면, 일부 해외 인쇄학술지의 경우 외국학술지지원센터(FRIC)에서
무료 원문복사 서비스를 제공합니다.

NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.

이 논문과 함께 출판된 논문 + 더보기