In non-destructive testing using infrared thermography, we deal with disturbances of the temperature field on the surface of the tested objects, which are not caused by subsurface defects. In order for the thermograms to be free from interference and to have clearly distinguished features of interest to us, a number of image processing algorithms are used. In the article, on the example of non-destructive testing of the GFRP composite by pulse thermography, the effectiveness of various image processing algorithms was compared. In the algorithms used, there is a mechanism to increase the signal/noise ratio and thus increase the effectiveness of defect detection. It should be noted that each processing of the thermogram leads to distortion and the point is only that this distortion is beneficial from the point of view of the purpose of non-destructive testing, i.e. detection of defects and evaluation of their parameters.

Using composite materials in turbine blades has become common in the wind power industry due to their mechanical properties and low weight. This work aims to investigate the effectiveness of the active infrared thermography technique as a non-destructive inspection tool to identify defects in composite material structures of turbine blades. Experiments were conducted, heating the sample and capturing thermographic images using a thermal camera. Numerical simulations were compared with experimental results. It was demonstrated that active infrared thermography is an efficient technique for detecting flaws in composite material structures of turbine blades. This research contributes to advancing knowledge in inspecting composite materials

This study delves into the utilization of solar loading thermography for inspecting concrete structures, specifically focusing on delamination detection via active thermography algorithms. Accounting for potentially impactful ambient environmental conditions, a numerical model is designed to enhance the accuracy of Infrared Thermography (IRT) measurements. The model also assists in identifying the most relevant times for infrared data collection, depending on whether the delaminated surface is facing North, South, East, or West, taking into consideration the sun's positional influence. Experimental data is employed to verify the validity of the proposed model. Furthermore, the study investigates the correlation between the heat flux absorbed by the surface and the resultant thermal contrast created by internal delamination.