## 1 Introduction  
Periodic monitoring and testing of materials and structures is very important for many industrial applications. Considering the aviation industry, namely regarding the fatigue of aircraft structures, prevention is particularly important, because cracks and damage can lead to dangerous situations, even to aircraft accidents. This is particularly true for the composite materials that are nowadays commonly used in aviation, where, due to the structure of composite materials consisting of two or more layers, produced from different materials with dissimilar chemical and physical properties, which are merged together, dangerous detachments of the layers can occur suddenly. The increased use of advanced composite materials in primary aircraft structures has initiated a discussion of how such structures perform under repeated loading, since there are many clear differences between composite and metal materials. This is the reason that multiple methodologies associating a specific design and loading scenario with an accurately predicted number of cycles to failure with an associated reliability level and considering the particularities of degradation of structural properties in composite materials, together with enhanced methods, have been developed. Research in the area of NDT (Non-Destructive Testing) has been mainly focused on the need to monitor their state in order to prevent critical damage. This article is focused on non-destructive testing, which means that the material properties are measured and determined without causing damage. In this area of non-destructive diagnostics, many techniques and methods have been developed [1; 2; 3; 4; 5]. The development of the technique includes the sensor design, integration (contact, contactless, built-in) and signal processing together with the evaluation of the obtained measurement results. In general, they are based on the principles of optical analysis, infrared thermography, ultrasonic scans, X-ray observations or electromagnetic principles, but each of these techniques has some limitations, involving, for example, the material type, dimensions or shape of the inspected area, resolution, duration, price, etc. Therefore, they are often integrated. Optical imaging methods including coherent imaging, speckle interferometry and holographic interferometry are also used for defect detection. These techniques show some limits in the case of in-field application, when large structures must be analyzed. They are often used, for example, in combination with ultrasonic [6] or laser-ultrasound [7] methods. On the other hand, thermography is based on the experimental observation of local variations in the thermal resistance of the structure caused by cracks or delimitations. A disadvantage is that only in the most recent and costly systems is the spatial resolution sufficient to allow reliable analysis of damages with small dimensions. The cooled or uncooled infrared sensors and corresponding techniques are also commonly used and improved [8], for example, from the signal-to-noise ratio point of view [9]. Moreover, many other enhanced thermography techniques have been developed [10; 11; 12]. Some of them are based on deep learning techniques [13] or on the active thermography approach [14; 15; 16], which involves a heat source and an infrared camera mounted to a mobile part of the system. X-ray radiography is based on the particular X-ray transparency of an object, which produces an image of the defect, but there is a safety hazard due to X-ray exposure, the costs are usually high, and the analysis of large surfaces is very difficult [17]. Therefore, it is usually used, for example, in combination with ultrasonic methods [18].