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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Vydáno v:Automation in construction Ročník 122; s. 103478
Hlavní autoři: Tejedor, Blanca, Barreira, Eva, Almeida, Ricardo M.S.F., Casals, Miquel
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.02.2021
Elsevier BV
Témata:
2D correlation coefficient
2D map
Anomalies
Automated data-processing technique
Automation
Building components
Data processing
Image quality
MATLAB
Measured U-value
Pixels
Processed image
Quality image
Quantitative infrared thermography
SURFER
Thermography
Processed image
Quality image
SURFER
Automated data-processing technique
2D correlation coefficient
MATLAB
Measured U-value
2D map
Quantitative infrared thermography
ISSN:0926-5805, 1872-7891
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Shrnutí: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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ISSN:0926-5805
1872-7891
DOI:10.1016/j.autcon.2020.103478