Obtaining 3D Dense Thermal Models of Interiors of Buildings Using Mobile Robots

Adán, Antonio; López-Rey, Alejandro; Ramón, Amanda

doi:10.1007/978-3-031-21065-5_1

Cited by 1 publication

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“…Very few works have appeared in the field of mobile thermal scanning platforms to date. The existing platforms concern terrestrial robots or unmanned aerial vehicle (UAV) platforms [6][7][8][9][10][11] which, with a greater or lesser extension, collect thermal data from the indoors or outdoors of buildings. In all these works, the temperature provided by the infrared camera, which is later inserted into each of the points of the TPC, is not corrected as regards different factors that affect the temperature value.…”

Section: Apparent Temperature In 3d Thermal Point Cloudsmentioning

confidence: 99%

Correction of Temperature from Infrared Cameras for More Precise As-Is 3D Thermal Models of Buildings

et al. 2023

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This paper studies how to create precise 3D thermal maps of building interiors by correcting the raw apparent temperature values yielded by the thermal cameras. This matter has not, to date, been dealt with in the literature, which leads us to conclude that the current methodologies that obtain thermal point clouds are incomplete and imprecise. Without a suitable correction, any further energy parameter calculation obtained from the thermal point cloud is incorrect. This paper presents a method that deals with important aspects to be corrected, such as the repeatability of thermal cameras, the use of the true emissivity of the materials sensed, and the inclusion of the reflected radiant energy caused by the environment. The method has been successfully tested in several indoor scenes using a thermal scanning platform. The results show that significant corrections of up to 8% of the raw temperature values must be carried out in the final thermal model, thus justifying the need for the correction. As an application of the method, an empirical calculation and a comparison of transmittances with and without temperature corrections are presented at the end of the paper. In this case, the relative errors with respect to the average nominal U-value decrease from 94% to 11%. The general conclusion is that precise calculations of energy parameters in which infrared cameras are involved must take these corrections to temperature into account.

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