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...
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| Published in: | Automation in construction Vol. 122; p. 103478 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Amsterdam
Elsevier B.V
01.02.2021
Elsevier BV |
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| ISSN: | 0926-5805, 1872-7891 |
| Online Access: | Get full text |
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| Abstract | 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%.
•A lack of non-complex diagnosis tools for entire wall areas with defects was detected.•A thermogram involves 76,800 elements with different TWALL for each instant “t”.•An automated data-processing method is proposed to identify the U-value distribution.•A mesh comprised of 1600 elements could be enough to compute a 2D U-value map.•Image quality losses are estimated at 6.65%. |
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| AbstractList | 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%. 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%. •A lack of non-complex diagnosis tools for entire wall areas with defects was detected.•A thermogram involves 76,800 elements with different TWALL for each instant “t”.•An automated data-processing method is proposed to identify the U-value distribution.•A mesh comprised of 1600 elements could be enough to compute a 2D U-value map.•Image quality losses are estimated at 6.65%. |
| ArticleNumber | 103478 |
| Author | Casals, Miquel Almeida, Ricardo M.S.F. Tejedor, Blanca Barreira, Eva |
| Author_xml | – sequence: 1 givenname: Blanca surname: Tejedor fullname: Tejedor, Blanca email: blanca.tejedor@upc.edu organization: Universitat Politècnica de Catalunya (UPC), Department of Project and Construction Engineering, Group of Construction Research and Innovation (GRIC), C/ Colom, 11, Ed. TR5, 08222 Terrassa, Barcelona, Spain – sequence: 2 givenname: Eva surname: Barreira fullname: Barreira, Eva organization: CONSTRUCT-LFC, University of Porto, Faculty of Engineering (FEUP), Civil Engineering Department, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal – sequence: 3 givenname: Ricardo M.S.F. surname: Almeida fullname: Almeida, Ricardo M.S.F. organization: CONSTRUCT-LFC, University of Porto, Faculty of Engineering (FEUP), Civil Engineering Department, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal – sequence: 4 givenname: Miquel surname: Casals fullname: Casals, Miquel organization: Universitat Politècnica de Catalunya (UPC), Department of Project and Construction Engineering, Group of Construction Research and Innovation (GRIC), C/ Colom, 11, Ed. TR5, 08222 Terrassa, Barcelona, Spain |
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| Keywords | Processed image Quality image SURFER Automated data-processing technique 2D correlation coefficient MATLAB Measured U-value 2D map Quantitative infrared thermography |
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