• DocumentCode
    723588
  • Title

    Statistical approach to endurance models - data processing using regression models

  • Author

    Trnka, Pavel ; Soucek, Jakub ; Hornak, Jaroslav ; Svoboda, Michal ; Koltunowicz, Tomasz ; Gutten, Miroslav

  • Author_Institution
    Fac. of Electr. Eng., Univ. of West Bohemia in Pilsen, Pilsen, Czech Republic
  • fYear
    2015
  • fDate
    20-22 May 2015
  • Firstpage
    238
  • Lastpage
    241
  • Abstract
    The paper presents a methodology for processing experimental data related to the issue of the electrical insulation system endurance, using the method of accelerated laboratory aging. Several possible approaches are proposed. Traditionally used is the phenomenological approach combined with mathematical regression of measured data. This method is complemented by confidence intervals to ensure statistical certainty of the results of the experiment statements. The paper also describes a statistical approach to endurance modeling, however similarly supplemented with statistical certainty by using confidence intervals. Statistical certainty based on confidence intervals brings very valuable information for the practical use of electrical insulation materials and systems, especially considering design and dimensioning.
  • Keywords
    ageing; insulating materials; regression analysis; accelerated laboratory aging method; data processing; electrical insulation material; electrical insulation system; electrical insulation system endurance model; mathematical regression model; statistical approach; statistical certainty; Accelerated aging; Degradation; Estimation; Insulation; Mathematical model; Weibull distribution; Degradation; Endurance; Laboratory Aging; Lifetime; Regression Model; Reliability Calculations; Statistical evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Power Engineering (EPE), 2015 16th International Scientific Conference on
  • Conference_Location
    Kouty nad Desnou
  • Type

    conf

  • DOI
    10.1109/EPE.2015.7161075
  • Filename
    7161075