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
Link To Document :
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