Metric contrast of thermal 3D models of large industrial facilities obtained by means of low-cost infrared sensors in UAV platforms

Monitoring for maintenance or studies of energy efficiency in buildings, large infrastructure, industrial facilities, etc., are common nowadays. These kind of studies are developed with inspections which determine the state of the facilities that are analysed. The difficulty is increased along with the size and complexity of the facility itself, and even more when the attribute to be surveyed is not noticeable or responsive for the human eye. In recent years, a series of techniques that rely on different sensors mounted on UAVs allow detecting problems that are associated with facilities of large dimensions. Almost all of them work in the visible band (RGB), but the generation of thermal 3D models permits detecting any heat anomaly related to the functioning of these facilities. This research proposes a methodology and workflow for the generation and Metric Contrast of Thermal Models (MCTM). This methodology is metrically applied to a mining-industrial facility in which thermal conditions have great influence for a proper functioning. For this metric contrast, several distances have been measured in the field and compared to those obtained from the models. The average difference between the true magnitude and those obtained from the RGB and thermal models are 5 and 31 cm, and their standard deviations are 7 and 29 cm, respectively. The comparison between the RGB and the thermal model provides an average distance between points is 0.19 m, and for 75% of the points the distance is lesser than 0.35 m. Although the RGB model is more accurate, the precision of the thermal model is enough for the objectives set.

Automated summary

Monitoring energy efficiency and maintenance of buildings, infrastructure, and industrial facilities is common nowadays and has become more advanced with the use of UAV-mounted sensors for detecting issues in large facilities. This research proposes a methodology for generating and comparing thermal models with good precision, particularly in mining-industrial facilities where thermal conditions are crucial. The average differences and standard deviations between true measurements and those obtained from RGB and thermal models are provided, showing that while the RGB model is more accurate, the thermal model is adequate for achieving the set objectives.