비파괴검사학회지 (Journal of the Korean Society for Nondestructive Testing)

  • 제27권6호
  • /
  • Pages.509-519
  • /
  • 2007
  • /
  • 1225-7842(pISSN)
  • /
  • 2287-402X(eISSN)
한국비파괴검사학회 (The Korean Society for Nondestructive Testing)
권호 표지

Neural Network Approach to Automated Condition Classification of a Check Valve by Acoustic Emission Signals

  • Lee, Min-Rae (Samsung Heavy Industry, Quality Assurance Team) ;
  • Lee, Joon-Hyun (School of Mechanical Engineering, Pusan National University) ;
  • Song, Bong-Min (School of Mechanical Engineering, Pusan National University)
  • 발행 : 2007.12.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper presents new techniques under development for monitoring the health and vibration of the active components in nuclear power plants, The purpose of this study is to develop an automated system for condition classification of a check valve one of the components being used extensively in a safety system of a nuclear power plant. Acoustic emission testing for a check valve under controlled flow loop conditions was performed to detect and evaluate disc movement for valve failure such as wear and leakage due to foreign object interference in a check valve, It is clearly demonstrated that the evaluation of different types of failure types such as disc wear and check valve leakage were successful by systematically analyzing the characteristics of various AE parameters, It is also shown that the leak size can be determined with an artificial neural network.

키워드

참고문헌

  1. Freeman, James A. and Skapura, David M. (1992) Neural Networks (Algorithm, Applications, and Programming Techniques), Addison-Wesley Publishing Company, pp. 89-125
  2. Haynes, H. D. (1992) Evaluation of Check Valve Monitoring Methods, Journal of Nuclear Engineering Design, Vol. 134, pp. 283-294 https://doi.org/10.1016/0029-5493(92)90146-M
  3. Lee, M. R. and Lee, J. H. (2002) Condition Monitoring of a Check Valve for Nuclear Power Plants by Means of Advanced Sensor Technique, Proceeding of ISOFIC, pp. 112-117
  4. Lee, M. R. and Lee, J. H. (2005), Condition Monitoring of a Nuclear Power Plant Check Valve Based on Acoustic Emission and a Neural Network, Journal of AMSE PVP, Vol. 127, pp. 230-236
  5. Lee, J. H., Lee, M. R. and Kim, J. T. (2004) Characteristics of Acoustic Emission from Check Valve Leaks at Nuclear Power Plants, Proceeding of ICAPP'04
  6. Pool, A. J. and Porwit, A. J. (1982), Prediction of Surge Pressure Form Check Valves for Nuclear, Journal of ASME, No. 62-WA-219
  7. Roy, Amitava, Barat, P. and Swapan, K. D. (1995), Material Classification Through Neural Networks, Journal of Ultrasonics, Vol. 22, No. 3, pp. 175-180
  8. Schwertzer, P. A. (1972) Handbook of Valves, Industrial Press Inc., New York, USA