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Determination of Maintenance Period and Failure Probability for Turbine Using Maintenance Record

터빈설비의 정비이력을 이용한 고장확률 예측 및 정비주기 설정에의 응용

  • Received : 2010.06.07
  • Accepted : 2010.07.22
  • Published : 2010.09.01

Abstract

The breakdown of any critical component of a turbine results in the outage of power plants. Unexpected failure decreases equipment utilization and causes enormous economic losses. Currently, we conduct conservative preventive maintenance for a maintenance period that is proposed by a vendor. In the rapidly changing business environment, reliability-based maintenance is required in order to remain competitive and reduce maintenance costs while maintaining the reliability of equipment. In order to determine an appropriate maintenance period for guaranteeing reliability, we must determine the failure probability by carefully analyzing the failure history of the equipment. In this study, we created a database of failure history for power-plant turbines, predicted the best repair time using the Weibull function, and investigated how the appropriate maintenance cycle can be determined.

터빈설비 각 중요부품의 고장은 발전정지라는 큰 파급효과를 유발하며, 예기치 못한 고장으로 설비의 이용률이 감소하게 되면 막대한 경제적 손실이 발생한다. 현재 발전설비는 제작사에서 제시한 정비주기를 기준으로 보수적인 예방정비를 실시하고 있으나, 급변하는 경영환경에서 경쟁력을 유지하기 위해서는 신뢰도를 유지하면서 정비비용을 절감하는 신뢰도 기반 정비방법을 도입 해야 할 필요가 있다. 신뢰성 있는 정비주기를 선정하기 위해서는 설비의 고장이력에 대한 면밀한 분석을 통하여 고장확률을 예측해야 한다. 본 논문은 발전설비 중 터빈 각 부품들의 고장이력을 데이터베이스로 만들고, Weibull 함수를 이용하여 최적의 정비시점을 예측하며, 정비주기를 결정하는 방법에 대하여 연구하였다.

Keywords

References

  1. Electric Power Research Institute, 2000, "Turbine- Generator Maintenance Interval Optimization Using a Financial Risk Assessment Technique," EPRI, Palo Alto, 1000820E204901, pp. 4-14
  2. Smith, A. M., Vasudevan, R. V., Matteson, T. D. and Gaertner, J. P., 1986, "Enhancing plant preventive maintenance via RCM," Proc. a. Reliab. Maintainab. Symp., Microelectronics Reliability, Volume 27, Issue 4, 1987, p. 785.
  3. Electric Power Research Institute, 2000, "Turbo-X User Manual Level 1," EPRI, 1000819, Polo Alto, pp. 6.1-6.7.
  4. Song, J. H. and Bark, J. H., 2007, "An Introduction to Reliability Engineering for Mechanical Engineer," Intervision, Seoul, pp.176-186
  5. Herder, P.M., van Luijk, J.A., Bruijnooge, J., 2008, "Industrial Application of RAM Modeling: Development and Implementation of a RAM Simulation Model for the $Lexan^{\circledR}$ Plant at GE Industrial, Plastics",Reliability Engineering & System Safety, Volume 93, Issue 4, pp. 501-508 https://doi.org/10.1016/j.ress.2006.10.019
  6. Martorell, S., Muñoz, A. and Serradell, V., 1995, "An Approach to Integrating Surveillance and Maintenance Tasks to Prevent the Dominant Failure Causes of Critical Components," Reliability Engineering & System Safety, Volume 50, Issue 2, pp. 179-187 https://doi.org/10.1016/0951-8320(95)00081-C

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