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Pulse thermography (PT) has proven to be a valuable non-destructive testing method to identify and quantify defects in fiber-reinforced polymers. To perform a quantitative defect characterization, the heat diffusion within the material as well as the material parameters must be known. The heterogeneous material structure of glass fiber-reinforced polymers (GFRP) as well as the semitransparency of the material for optical excitation sources of PT is still challenging. For homogeneous semitransparent materials, 1D analytical models describing the temperature distribution are available.
Here, we present an analytical approach to model PT for laterally inhomogeneous semitransparent materials.We show the validity of the model by considering different configurations of the optical heating source, the IR camera, and the differently coated GFRP sample. The model considers the lateral inhomogeneity of the semitransparency by an additional absorption coefficient. It includes additional effects such as thermal losses at the samples surfaces, multilayer systems with thermal contact resistance, and a finite duration of the heating pulse. By using a sufficient complexity of the analytical model, similar values of the material parameters were found for all six investigated configurations by numerical fitting.
The paper presents a numerical method to detect and characterise defects and inhomogeneities by means of active thermography. The objective was to determine the wall thickness of structure elements with an inaccessible back wall, e.g., elements of pipes or containers. As test specimens we used PVC samples with the thickness of about 2 cm that had spatial variations in the back wall geometry. Flash lamps provided the heating. To measure the thickness of the wall, we employed the LevenbergMarquardt method, which we applied here to experimental thermographic data for non-destructive testing. We started the inversion procedure by making a rough first estimation of the back wall geometry following the echo defect shape method, and then we calculated the thickness of the back wall. We found reasonable reconstruction results which differed from the real value significantly below 1 mm at the defect centre, whereas the error wais increased at the edge of the defect, depending on its shape and depth.