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Failure Rate Calculation using the Mixture Weibull Distribution

혼합 와이블 분포를 이용한 고장률 산출 기법에 관한 연구

  • Chai, Hui-seok (Dept. of Electrical Engineering, Soongsil Univ.) ;
  • Shin, Joong-woo (Dept. of Electrical Engineering, Soongsil Univ.) ;
  • Lim, Tae-jin (Dept. of Industrial Information System Engineering, Soongsil University) ;
  • Kim, Jae-chul (Dept. of Electrical Engineering, Soongsil University)
  • Received : 2016.12.21
  • Accepted : 2017.02.12
  • Published : 2017.03.01

Abstract

In 2014, ISO 55000s has been enacted and the power plant asset management is becoming a hot issue for all over the world. The asset management system is being developed as a combination of CBM(Condition Based Maintenance) and RCM(Reliability Centered Maintenance). Therefore, the research on the calculation of the failure rate which is the most basic index of RCM is actively carried out. The failure rate calculation has been going on for a long time, and the most widely used probability distribution is the Weibull distribution. In the Weibull distribution, the failure rate function is determined in three types according to the value of the shape parameter. However, the Weibull distribution has a limitation that it is difficult to apply it when the trend of failure rate changes-such as bathtub curves. In this paper, the failure rate is calculated using the mixture Weibull distribution which can appropriately express the change of the shape of the failure rate. Based on these results, we propose the necessity and validity of applying mixture Weibull distribution.

Keywords

References

  1. J. H. Sun, "Technical Trend in Asset Management of Power Equipment", Journal of the Electric World, Special Issues, 2015.
  2. KEPCO, "Development of Optimal investment strategy model and system in distribution network", KEPCO Technical Report, 2007.
  3. D. J. Kwon, "Development for the Eco-Design-low loss 154kV Transformers", 2016 Cigre conference, 2016. 11.
  4. J. R. Jung, "Improvement to Partial Discharge Measurements for Factory and Site Acceptance Tests of Power Transformers", 2016 Cigre Conference, 2016. 11.
  5. H. T. Lee, J. C. Kim, J. F. Moon, and C. H. Park, "Analyzing of the Time Varying Failure Rate of Components of Power Distribution System using Weibull Distribution", KIEE Autumn Conference, 2003.
  6. H. S. Chai, J. W. Shin, J. C. Kim, K. W. Choi, and J. F. Moon, "Study on the Random/Wear-out Failure Rate Calculation by Fault Management", KIEE Summer Conference, 2016. 07.
  7. H. W. Jeong, J. M. Cha, B. H. Chang, and J. S. Choi, "A Study on the Reliability Calculation of ESS using the Component-Specific Failure Rate", KIEE Summer Conference, 2016.07.
  8. S. Y. Mou, "Modeling of Failure Rate Estimation Method for Power Transformer", Gachon University Master Thesis, 2016.08.
  9. J. C. Kim, "Measurement of Time-Varing Failure Rate for Power Distribution System Equipment Considering Weather Factor", KIIEE, Vol. 23, No. 8, 2009.08.
  10. H. T. Lee, J. F. Moon, J. C. Kim, "Deciding the Maintenance Priority of Power Distribution System using Time-varying Failure Rate", KIEE Vol. 55A, No. 11, 2006.11.
  11. K. W. Choi, H. S. Chai, I. S. Hwang, J. F. Moon, "A Study on Failure Rate Extraction of Electric Power Distribution System Equipment Considering Various Factors", KIIEE Spring Conference, 2016.05.
  12. R. Jiang, and D. N. P. Murthy, "Modeling Failure-Data by Mixture of 2 Weibull Distributions: A Graphical Approach", IEEE Trans. on Reliability, Vol. 44, No. 3, 1995. 09.
  13. A. M. Razali, Ali A. Salih, A. A. Mahdi, A. Zaharim, K. Ibrahim, and K. Sopian, "On Simulation Study of Mixture of Two Weibull Distributions", the 7th WSEAS ICOSSSE '08, 2008. 08.
  14. N. Dwidayati, S. H. Kartiko, and Subanar, "Estimation of the Parameters of a Mixture Weibull Model for Analyze Cure Rate", Applied Mathematical Sciences, Vol. 7, No. 116, 2013.
  15. J. A. Carta, and P. Ramirez, "Analysis of Two- Component Mixture Weibull Statistics for Estimation of Wind Speed Distributions", Renewable Energy, Vol. 32, Issue 3, 2007. 03.
  16. H. S. Song, and S. D. Kwon, "Wind Energy Assessment at Complex Terrain using Mixture Probability Distribution", Journal of the KSES, Vol. 33, No. 2, 2013. 04.
  17. H. S. Jung, Y. I. Kwon, and D. H. Park, "Reliability Test Analysis Evaluation", Young Ji Publishers, 2009. 02.