전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제56권2호
  • /
  • Pages.248-253
  • /
  • 2007
  • /
  • 1975-8359(pISSN)
  • /
  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

Markov State Model을 이용한 복합화력 발전설비의 최적의 유지보수계획 수립

Application Markov State Model for the RCM of Combustion Turbine Generating Unit

  • 이승혁 (한양대 공대 전기공학과) ;
  • 신준석 (한양대 공대 전기공학과) ;
  • 김진오 (한양대 공대 전기공학과)
  • 발행 : 2007.02.01
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초록

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

키워드

참고문헌

  1. Yhomas M. Welte, J$\phi$m Vatn and J$\phi$m Heggset, 'Markov State Model for Optimization of Maintenance and Renewal of Hydro Power Components,' $9^{th}$ PMAPS KTH, Stockholm, Sweden, 11-15 June, 2006
  2. A. Grall, L. Dieulle, C. Berenguer and M. Roussignol, 'Continuous time predictive-maintenance scheduling for a deteriorating system,' IEEE Trans. Reliability, vol. 51, pp. 141-150, June 2002 https://doi.org/10.1109/TR.2002.1011518
  3. M. Rausand, 'Reliability centered maintenance,' Reliability Engineering and System Safety, vol. 60, pp. 121-132, 1998 https://doi.org/10.1016/S0951-8320(98)83005-6
  4. R. Billinton and R. N. Allan, Reliability Evaluating . of Engineering System, Plenum Press, 1992
  5. M. J. Crowder, A. c. Kimber, R. L. Smith and T. J. Sweeting, Statistical Analysis of Reliability Data, Chapman and Hall, 1991
  6. M. Rausand and A. H$\phi$yland, System Reliability Theory, Wiley-Interscience 2004