Modelling of heat flux in building using soft-computing techniques

Authors:
Javier Sedano;José Ramón Villar;Leticia Curiel;Enrique de la Cal;Emilio Corchado
Affiliations:
Department of Electromechanical Engineering, University of Burgos, Burgos, Spain;Department of Computer Science, University of Oviedo, Spain;Department of Civil Engineering, University of Burgos, Burgos, Spain;Department of Computer Science, University of Oviedo, Spain;Department of Computer Science and Automation, University of Salamanca, Salamanca, Spain
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Year:
2010

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Abstract

Improving the detection of thermal insulation failures in buildings includes the development of models for heating process and fabric gain -heat flux through exterior walls in the building-. Thermal insulation standards are now contractual obligations in new buildings, the energy efficiency in the case of buildings constructed before the regulations adopted is still an open issue, and the assumption is that it will be based on heat flux and conductivity measurement. A three-step procedure is proposed in this study that begins by considering the local building and heating system regulations as well as the specific features of the climate zone. Firstly, the dynamic thermal performance of different variables is specifically modeled. Secondly, an exploratory projection pursuit method called Cooperative Maximum-Likelihood Hebbian Learning is used to extract the relevant features. Finally, a supervised neural model and identification techniques are applied, in order to detect the heat flux through exterior walls in the building. The reliability of the proposed method is validated for a winter zone, associated to several cities in Spain.