Implementation of the boundary element method for detecting defects by transient thermography on an aluminum plate

Aparicio, Jorge Humberto Vargas; Arroyo, Lesli Ortega; León, Helvio Ricardo Mollinedo Ponce de; Herrera, Jorge Martínez; Arias, Yonatan Alí Rodríguez; González, Sandra Arellano; Rodríguez‐Romo, Suemi; Castaño, V. M.

doi:10.1007/s10973-016-5538-z

Cited by 5 publications

(1 citation statement)

References 37 publications

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“…Therefore, from an image with the pixels representing different temperature values of the surface under study, IRT is a technique with a wide range of applications [26]: (1) civil engineering and buildings [1,15,[17][18][19]22], (2) IRT applied to different types of material [22,[27][28][29][30][31][32][33], (3) industrial applications [34][35][36], (4) environment [37][38][39] and (5) biomedical applications [40][41][42][43]. In the following subsection, a brief review with regard to the most recent IRT works that detect moisture areas affecting the surfaces of different construction materials is described.…”

Section: Bilateral Filtering Technique Applicationmentioning

confidence: 99%

Automatic detection of moistures in different construction materials from thermographic images

Garrido

Lagüela

Сфарра

et al. 2019

J Therm Anal Calorim

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Moisture is a pathology that damages all type of construction materials, from materials of building envelopes to materials of bridges. Its presence can negatively affect the users' conditions of indoor comfort. Furthermore, heating and cooling energy demand can be increased by the presence of moist materials. Infrared thermography (IRT) is a common technique in the scientific field to detect moisture areas, because of its non-destructive, non-contact nature. In addition, IRT allows an earlier moisture detection compared to the analysis using visible images. In order to optimize thermographic inspections, this paper presents one of the first methodologies for the automatic detection of moisture areas affecting the surface of construction materials. The methodology is based on the application of visible image processing techniques adapted to thermographic images through the consideration of an image conversion format, a thermal criterion and a thermal and a geometric filter. The precision, recall and F-score parameters obtained are around 83.5%, 73.5% and 72.5%, respectively, considering the false positives/negatives through a series of 12 tests made in different construction materials and ambient conditions, comparing the preliminary results with existing methodologies. Keywords Moisture Á Infrared thermography Á Automation Á Adapted visible image processing Á Construction materials Á Different environmental conditions & I. Garrido

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