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Regression methods for improved lifespan modeling of low voltage machine insulation

Salameh, Farah and Picot, Antoine and Chabert, Marie and Maussion, Pascal Regression methods for improved lifespan modeling of low voltage machine insulation. (2015) Mathematics and Computers in Simulation, vol. 131. pp. 200-2016. ISSN 0378-4754

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Official URL: http://dx.doi.org/10.1016/j.matcom.2015.11.001

Abstract

This paper deals with the modeling of insulation material lifespan in a partial discharge regime under certain accelerated electrical stresses (voltage, frequency and temperature). An original model, relating the logarithm of the insulation lifespan, the logarithm of the electrical stress and an exponential form of the temperature, is considered. An estimation of the model parameters is performed using three methods: the design of experiments (DoE) method, the response surface method (RSM) and the multiple linear regression (MLR) method. The estimation is obtained on learning sets determined according to each method specification. The performance, in terms of estimation, of each of the three methods is evaluated on a test set composed of additional experiments. For economic reasons and fl exibility, the learning and test sets are composed of experiments carried out on twisted pairs of wires covered by an insulator varnish. The ability of the DoE and the RSM methods to organize and to limit the number of experiments is confirmed. The MLR method, however, shows more flexibility with regard to the studied configurations. Thus, it offers an efficient solution when organization is not required or not possible. Moreover, the fl exibility of MLR allows specifi c ranges for the factors to be explored. A local analysis of the estimation performance shows that very short and long lifespans cannot be simultaneously represented by the same model.

Item Type:Article
Additional Information:Thanks to Elsevier editor. The definitive version is available at http://www.sciencedirect.com The original PDF of the article can be found at : http://www.sciencedirect.com/science/article/pii/S0378475415002372
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: Pascal MAUSSION
Deposited On:26 Aug 2016 10:56

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