본문 바로가기
KERD
논문KCI 등재

LNG FPSO 압축기 고장시간 예측 방안에 관한 연구

A Study on Estimating the Next Failure Time of a Compressor in LNG FPSO

0

조회

0

다운로드

4

인용

0

참고문헌

키워드

주제분류산업공학

초록

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and moreefforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previousstudies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to theemerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data ofequipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to havingmuch concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM(Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressorwhich is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloadingvessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.

Abstract

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and moreefforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previousstudies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to theemerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data ofequipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to havingmuch concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM(Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressorwhich is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloadingvessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.

참고문헌 (34)

  1. Antoine, G., "Continuous-time predictive-maintenance scheduling for a deteriorating system", IEEE Transactions on Reliability, 51(2), pp.141~150 (2002)
  2. Arunraj, N.S., "Risk-based maintenance policy selection using AHP and goal programming", Safety Science, 48(2), pp.238~247 (2010)
  3. Bae, J.H., "A study on risk quantifying method for the worker accidents of offshore plant considering uncertainty", Proceedings of the society of naval architects of Korea, pp.113~118 (2012)
  4. Carey, B., "Condition-based maintenance of machines using hidden markov models", Mechanical Systems and Signal Processing, 14(4), pp.597~612 (2000)
  5. Choe, B.H., "Probabilistic Assessment of life Time for Gas Pipe Lines", Proceedings of Trans. Korean Soc. Mech. Eng, pp.234~239 (2004)
  6. Dey, P. K., "Riskbased maintenance model for offshore oil and gas pipelines : a case study", Journal of Quality in Maintenance Engineering, 10(3), pp.169~183 (2004)
  7. Durdjanovic, D., "Watchdog agent-an infotronics-based prognostics approach for product performance degradation assessment and prediction", Advanced Engineering Informatics, 17(3-4), pp.109~125 (2003)
  8. Fu, C., "Predictive maintenance in intelligent-control- maintenance-management system for hydroelectric generating unit", IEEE Transactions on Energy Convertsion, 19(1), pp.179~186 (2004)
  9. Goncharenko, I., "Remote maintenance for IM", Proceedings of the first international symposium on environmentally conscious design and inverse manufacturing (EcoDesign’99), pp.862~867 (1999)
  10. Grall, A., "Continuous-time predictive-maintenance scheduling for a deteriorating system", IEEE Transactions on Reliability, 51(2), pp.141~150 (2002)
  11. Hussin, H., "A systematic and practical approach of analyzing offshore system maintenance data", Proceedings of the International Multiconference of Engineers and Computer Scientists, 3 (2010)
  12. ISO, "ISO Standard : Mechanical Vibration of Non- Reciprocating Machine-Measurements on Rotating Shafts and Evaluation", ISO 7919, ~ (1996)
  13. Jang, D.H., "Developing the maintenance system for offshore plant and ship", Proceedings of the society of naval architects of Korea, pp.1262~1271 (2011)
  14. 전정익, "선박해양구조물의 제품수명주기 내 유지보수 정보 획득을 위한 PEID에 관한 연구", 한국해양공학회지, 26(5), pp.63~72 (2012), 한국해양공학회
  15. Jun, H. B., "A predictive algorithm for estimating the quality of vehicle engine oil", Journal of Industrial Engineering : Theory, Applications and Practice, 15(4), pp.386~396 (2009)
  16. CBM approach for facility equipment, "Kim, Y.S.", 96~103, pp.Technical report. Procon co., No. 2 (2012)
  17. Koc, M., "A system framework for next-generation E-maintenance systems", Transaction of Chinese Mechanical Engineer, 12(5) (2001)
  18. Vibration and maintenance handbook for field engineers, "Lee, B.J", 18~94 (1999)
  19. Lee, H. W., "MTBF estimator in reliability growth model with application to Weibull process", Journal of the Korean Society for Quality Management, 26(3), pp.71~81 (1998)
  20. Lee, K.H., "A study on augmented reality technologies in the operation and maintenance phase of offshore plants", Proceedings of the society of naval architects of Korea, pp.106~111 (2011)
  21. Lee, J., "E-intelligence strategies for product and manufacturing innovation", Transaction of Chinese Mechanical Engineer, 12(5), pp.526~531 (2001)
  22. Lee, S.K., "State-of-the-art for LNG-FPSO technology", Journal of the Korean Society of Marine Engineering, 36(1), pp.62~78 (2012)
  23. Lin, D., "An approach to signal processing and condition-based maintenance for gearboxes subject to tooth failure", Mechanical Systems and Signal Processing, 18(5), pp.993~1007 (2004)
  24. Lu, H., "Real-Time Performance Reliability Prediction", IEEE Transaction on Reliability, 50(4), pp.353~357 (2001)
  25. Moan, T., "Reliability-based management of inspection, maintenance and repair of offshore structures", Structure and Infrastructure Engineering, 1(1), pp.33~62 (2005)
  26. Mobley, R.K., "An Introduction to Predictive Maintenance" (2002), Elsevier science publisher
  27. 박성환, "부식과 도장을 고려한 선체잔여수명예측시스템 설계", 대한조선학회 논문집, 50(2), pp.104~110 (2013), 대한조선학회
  28. Rouhan, A., "Probabilistic modeling of inspection results for offshore structures", Structural safety, 25(4), pp.379~399 (2003)
  29. Saranga, H., "Reliability prediction for condition-based maintained systems", Reliability Engineering and System Safety, 71(2), pp.219~224 (2001)
  30. 서광규, "유전 알고리즘에 의한 플랜트 보전을 위한 최적검사기간 결정 방법론", 산업경영시스템학회지, 26(2), pp.1~8 (2003), 한국산업경영시스템학회
  31. Suprasad, V., "Cost effective condition based maintenance using markov decision processes", Proceedings of IEEE Annual Maintainability Symposium on RAMS, pp.464~469 (2006)
  32. Survey on predictive maintenance technologies for production plant, "Toshio, T.", New-tech co, 100~108 (2010)
  33. Wang, W., "Reliability data analysis and modelling of offshore oil platform plant", Journal of Quality in Maintenance Engineering, 6(4), pp.287~295 (2000)
  34. Yang, B.S., "Condition monitoring and diagnostics" (2006), Intervision publisher

관련 논문AI추천

이 간행물의 다른 논문 (30건)