Variable Importance Assessment in Lifespan Models of Insulation Materials: A Comparative Study

Abstract : This paper presents and compares different methods for evaluating the relative importance of variables involved in insulation lifespan models. Parametric and non-parametric models are derived from accelerated aging tests on twisted pairs covered with an insulating varnish under different stress constraints (voltage, frequency and temperature). Parametric models establish a simple stress-lifespan relationship and the variable importance can be evaluated from the estimated parameters. As an alternative approach, non-parametric models explain the stress-lifespan relationship by means of regression trees or random forests (RF) for instance. Regression trees naturally provide a hierarchy between the variables. However, they suffer from a high dependency with respect to the training set. We show that RF provide a more robust model while allowing a quantitative variable importance assessment. Comparisons of the different models are performed on different training and test sets obtained through experiments.
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10th IEEE International Symposium on Diagnostics, Power Electronics and Drives (SDEMPED 2015), Sep 2015, Guarda, Portugal. Proceedings of 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, pp.198-204, 2015, 〈10.1109/DEMPED.2015.7303690〉
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Farah Salameh, Antoine Picot, Marie Chabert, Eve Leconte, Anne Ruiz-Gazen, et al.. Variable Importance Assessment in Lifespan Models of Insulation Materials: A Comparative Study. 10th IEEE International Symposium on Diagnostics, Power Electronics and Drives (SDEMPED 2015), Sep 2015, Guarda, Portugal. Proceedings of 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, pp.198-204, 2015, 〈10.1109/DEMPED.2015.7303690〉. 〈hal-01375415〉

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