• DocumentCode
    1716456
  • Title

    An alternative method for estimating mean life of power system equipment with limited end-of-life failure data

  • Author

    Cota-Felix, J.E. ; Rivas-Davalos, F. ; Maximov, S.

  • Author_Institution
    Morelia Inst. of Technol., Morelia, Mexico
  • fYear
    2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Traditional statistical reliability analysis relies on failure data for a population of devices. If a complete data set is available, statistical reliability analysis can provide predictions, such as mean-time-to-failure for a particular device, percentages of devices that will fail at a particular time or before a particular age, a statistical distribution of failure ages, and other statistical measures of device failures. However, a typical population includes devices that have not yet failed. In reliability analysis, such populations are often denoted as ldquoright censored populationsrdquo. In this paper, we propose a new method to evaluate mean life of power system equipment with limited end-of-life failure data. The method is based on the generalized exponential distribution. This method can be used as an alternative to methods based on normal and Weibull distribution models.
  • Keywords
    ageing; estimation theory; failure analysis; life cycle costing; power apparatus; power system management; distribution systems; end-of-life failure data; equipment aging; generalized exponential distribution; power system equipment mean life estimation; Failure analysis; Life estimation; Particle measurements; Power system analysis computing; Power system measurements; Power system modeling; Power system reliability; Power systems; Statistical distributions; Time measurement; Equipment aging; Weibull distribution; distribution systems; generalized exponential distribution; life data analysis; power systems; reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2009 IEEE Bucharest
  • Conference_Location
    Bucharest
  • Print_ISBN
    978-1-4244-2234-0
  • Electronic_ISBN
    978-1-4244-2235-7
  • Type

    conf

  • DOI
    10.1109/PTC.2009.5281863
  • Filename
    5281863