Automated data-processing technique: 2D Map for identifying the distribution of the U-value in building elements by quantitative internal thermography
Computing a 2D colour map of average U-values pixel-by-pixel could become a challenging task in terms of complexity and time, especially for entire façades under the influence of anomalies. In a quantitative IRT test, a thermal image with a resolution of 320 × 240 pixels involves 76,800 elements wit...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2020 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/334178 |
| Acesso em linha: | https://hdl.handle.net/2117/334178 https://dx.doi.org/10.1016/j.autcon.2020.103478 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Facades Heat -- Transmission Thermography Buildings -- Energy conservation Quantitative infrared thermography Automated data-processing technique Measured U-value Processed image 2D map 2D correlation coefficient Quality image MATLAB SURFER Façanes Calor -- Transmissió Termografia Edificis -- Estalvi d'energia Àrees temàtiques de la UPC::Edificació |
| Resumo: | Computing a 2D colour map of average U-values pixel-by-pixel could become a challenging task in terms of complexity and time, especially for entire façades under the influence of anomalies. In a quantitative IRT test, a thermal image with a resolution of 320 × 240 pixels involves 76,800 elements with different TWALL for each instant “t”. This research aims to create a thermographic 2D U-value map for the characterization of heavy walls in a stationary regime. The method was divided into three steps: (i) metrology; (ii) assessment of how mesh discretization affects the image quality by MATLAB; (iii) development of a 2D map by SURFER. The results demonstrated that all 2D maps were a great reproduction of the original image, considering as optimum a TWALL mesh comprised of 1600 elements of 8 × 6 pixels. The automated data-processing method only took 20 min and image quality losses were estimated at 6.65% |
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