Neuro-fuzzy approach for the characterization of building materials

  • Authors:

  • Adama Traore;Stéphane Grieu;Olivier Faugeroux;Bernard Claudet;Jean-Luc Bodnar

  • Affiliations:

  • ELIAUS Laboratory, University of Perpignan Via Domitia, France;ELIAUS Laboratory, University of Perpignan Via Domitia, France;ELIAUS Laboratory, University of Perpignan Via Domitia, France;ELIAUS Laboratory, University of Perpignan Via Domitia, France;GRESPI Laboratory, University of Reims Champagne Ardennes, France

  • Venue:
  • Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
  • Year:
  • 2009

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Abstract

The actual European energy context highlights the building sector as one of the largest sectors of energy consumption. Consequently, the “Energy Performance of Buildings Directive”, focusing on energy use in buildings, requires all the EU members to enhance their building regulations and to introduce energy certification schemes, with the aim of both reducing energy consumption and improving energy efficiency. That is why carrying out an energy performance diagnosis is mandatory. Indeed, invisible defaults could have a detrimental effect on insulating qualities. An in-situ estimation of thermo-physical properties allowing to locate defaults, the present work focuses on testing neuro-fuzzy systems to estimate the thermal diffusivity of building materials using thermograms obtained thanks to a non-destructive method.