Alarm Diagnosis of RCP Monitoring System using Self Dynamic Neural Networks

자기 동적 신경망을 이용한 RCP 감시 시스템의 경보진단

  • Published : 2000.09.01

Abstract

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

Keywords

References

  1. Eric B. Barflett, Robert E. Uhrig, 'Nuclear Power Plant Status Diagnostic using an Artificial Neural Network', Nuclear Technology, Vol. 97, 1992
  2. Robert E. Uhrig, 'Potential Application of Neural Networks to the Operation of Nuclear Power Plants', Nuclear Safety, Vol.32 No. 1, 1991
  3. 김정택 외 '고장진단기술 개발 방법 및 현황', 한국원자력발전소 , KAERI/AR-503/98 , 1998
  4. Kim, Keehoon and Eric B.Bartlett 'Nuclear Power Plant Fault Diagnosis Using Neural Networks with Error Estimation by Series Association ' IEEE Trans on Nuclear Science , Vol. 43, No.4 1996 https://doi.org/10.1109/23.531786
  5. Liang Jin, Peter N. Nikiforuk, and Madan M. Gupta, 'Dynamic and Stability of Mutilayered Recurrent Neural Networks,' in Proc 1993 IEEE Int. Conf. Neural Net., VolII, pp. 11358-1140, 1993
  6. George A. Rovithakis and A. Christodoulou, 'Adaptive Control of Unknown Plants Using Dynamical Neural Networks,' IEEE Trans. on SMC, Vol. 24 No. 3, pp. 400-411, March, 1994 https://doi.org/10.1109/21.278990
  7. L.Ljung, 'Issue in system identification,' IEEE Contr. Syst. Mag., Vol. 11, pp. 270-280, 1989
  8. S. I Sudharsanan and M. K. Sundareshan, 'Training of a three layer Dinamical recurrent neural network for nonlinear input-output mapping,' in Proc. Int. Joint. Conf. Neural Networks(IJCNN-91), vol.II, pp. 111-116. Seatle, WA 1991 https://doi.org/10.1109/IJCNN.1991.155322
  9. 성승환, 구인수외 3인' 신경망을 이용한 빠른 속도의 부하추종운전모사 기법 개발' 한국원자력학회 '98 추계학술대회 1998
  10. 이철권, 하재홍, 박진석, 구인수 '냉각재펌프 진동진단의 온-라인화에 관한 연구' 한국원자력학회 '97 춘계학술대회 1997. 5
  11. 성승환, 서용석, 구인수'SMART 인간기계 연계체계' 대한 기계학회 기계저널 1999.3
  12. 유동완, 김동훈, 이철권, 성승환, 서보혁 '자기 동적신경망을 이용한 RCP의 경보진단 시스템' 대한전기학회 하계학술대회 논문집 2000.7.19 pp2448-2491