Eliciting a human understandable model of ice adhesion strength for rotor blade leading edge materials from uncertain experimental data

Authors:
Ana M. Palacios;José L. Palacios;Luciano Sánchez
Affiliations:
Departamento de Informática, Universidad de Oviedo, 33071 Gijón, Asturias, Spain;Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA 16802, USA;Departamento de Informática, Universidad de Oviedo, 33071 Gijón, Asturias, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

The published ice adhesion performance data of novel ''ice-phobic'' coatings varies significantly, and there are not reliable models of the properties of the different coatings that help the designer to choose the most appropriate material. In this paper it is proposed not to use analytical models but to learn instead a rule-based system from experimental data. The presented methodology increases the level of post-processing interpretation accuracy of experimental data obtained during the evaluation of ice-phobic materials for rotorcraft applications. Key to the success of this model is a possibilistic representation of the uncertainty in the data, combined with a fuzzy fitness-based genetic algorithm that is capable to elicit a suitable set of rules on the basis of incomplete and imprecise information.