# Active Thermography for the Detection of Sub-Surface Defects on a Curved and Coated GFRP-Structure
## 4 Results and Discussion
### Detectability of Sub-Surface Defects in Front Perspective  
At first, test series 1 and 2 were carried out to see if defects beneath a coated surface can be detected by means of long-pulse thermography from a front perspective. Figure 6 shows the results of the first series of measurements at an excitation time of \(t_{\text{exc}}=15\,\text{s}\) and a distance \(k=89\,\text{mm}\) between excitation unit and test specimen. Figure 6a shows the first  
Figure 5: Signal flow diagram of the image processing operations. thermogram recorded by the infrared camera, i.e., at \(t_{rec}=0\,\)s as an example. Most of the specimen, except its edges, stands out from its surroundings due to a higher temperature. Since the heating is inhomogeneous due to the curvature of the specimen and at the same time the emissivity of the specimen is dependent on the angle, the edges of the specimen appear cooler than the background. In the x-direction, the specimen has a thermal profile typical for the specimen's curvature: the center of the specimen is warmest because it is closest to the excitation, while the temperature decreases towards the edges. The defects inserted from behind in the form of drilled holes are already visible in the raw image due to local temperature variations on the surface of the test specimen. They stand out from their surroundings as bright spots due to their higher temperature. The emerging defects do not have a sharp boundary to their surroundings. Mainly the lateral heat flow due to spatially inhomogeneous heating, but also the specimen's material (heat propagation in fiber direction) and curvature as well as the defect shape (conical defects that become larger with increasing depth, see Table 1) as well as the defect depth affect the appearance of the defects in the image of the surface temperature distribution. Figure 6b shows the result of the highest contrast single picture pre-processing method (reference method) without filtering. The defects are notable as in the raw thermogram in Figure 6a. Figure 6c shows the highest contrast single picture pre-processed image with filtering, automatic defect detection and calculated CNR (reference image with filtering). All defects are detected in each of the investigated parameter combinations of this image processing path in test series 1. It is noticeable that the value of the CNR decreases from defect 1 to defect 3. Since all defects are located at the same depth about 1.5 mm below the surface, the difference in CNR is due to the different diameters of the defects. Defect 1 with the largest diameter accordingly has the largest CNR value. This correlates with the depth-to-diameter ratio, and the smaller the depth-to-diameter ratio is, the better the defect is detected. The largest depth-to-diameter ratio in ROI A has defect 3 with a value of 0.75, which is in the range of the maximal reported ratios in the current research. To increase the contrast of the image series, PCA is applied; see Figure 6d. As a result, not only do the defect areas stand out more clearly, but also the fiber structure of the upper GFRP layer of the test specimen is additionally revealed. Figure 6e shows the PCA-based image with filtering, automatic defect detection and calculated CNR. The effect of PCA can be seen in the sharp increase in CNR values, e.g., from 189 to 2519 for defect 1. As for the reference image, the CNR values decrease as the depth-to-diameter ratio of each defect increases. While the increase in contrast might be less relevant for test series 1, since all defects are already detectable in the reference image without filtering, the contrast increase is more important in test series 2. Figure 7 shows the results of the second test series with an excitation time of \(t_{\text{exc}}=25\,\)s and a distance \(k=89\,\)mm between excitation unit and test specimen. In Figure 7a, as well as in the ROI B in Figure 7b, the typical temperature distribution for a curved surface can be seen, as in the previous test series.