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Trouble-free operation of electroinsulating subsystems is necessary for proper operation of the power system. Insulation systems are one of the most important elements of power system. For this reason, it is the effort to establish the most sophisticated diagnostic system. This system should be able to inform the maintenance of a possible failure. In this paper is present a physical model of thermal aging and statistical model using Weibull distribution. From these models of aging was then designed a new probabilistic model using thermal aging. Furthermore, this article describes the experiment and application of measurement data to the new designed model.

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.

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