• DocumentCode
    2005336
  • Title

    Competing risk model for long-stop-short-run systems

  • Author

    Guo, Chiming ; Wang, Xiaolin ; Guo, Bo

  • Author_Institution
    Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2011
  • fDate
    24-25 May 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Long-stop-short-run(LSSR) system is a kind of system that is longtime non-working and short time operating. It is important to study the reliability of LSSR system in some safety critical areas. There exist manifold failure mechanisms in the LSSR system. In this paper, a competing risk model is proposed to describe the reliability of the LSSR system. LSSR system presents two main kinds of failure modes: degradation failure and sudden failure. The degradation is described by stochastic Gamma process, and the sudden failure is described by Weibull distribution. In order to consider the influence of unknown degradation mechanisms to the reliability, Bayesian method is used to update the Weibull model parameters based on records of history values. The posterior distribution is used to estimate the expected reliability for the sudden failure mode. This competing risk model is illustrated by a pump case. Compared with the traditional method, the result of competing risk model is more appropriate for the reality.
  • Keywords
    Bayes methods; Weibull distribution; failure analysis; pumps; reliability; risk analysis; stochastic processes; Bayesian method; LSSR system reliability; Weibull distribution; Weibull model parameters; competing risk model; failure mechanisms; long-stop-short-run systems; posterior distribution; power station; pump; stochastic Gamma process; Equations; Mathematical model; Parameter estimation; Bayesian update; Gamma process; Long-stop-short-run; Weibull; competing risk;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Prognostics and System Health Management Conference (PHM-Shenzhen), 2011
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-7951-1
  • Electronic_ISBN
    978-1-4244-7949-8
  • Type

    conf

  • DOI
    10.1109/PHM.2011.5939496
  • Filename
    5939496