# Active Thermography for the Detection of Sub-Surface Defects on a Curved and Coated GFRP-Structure
## 4 Results and Discussion
### Influence of the Excitation Time on Sub-Surface Defect Detectability  
In test series 1 and 2, both different excitation times and different distances between the excitation unit and the test specimen were investigated. However, changing the distance \(k\), which modulates the energy introduction into the test specimen, proved to be impractical especially in the in situ application. Therefore, the focus is now on the investigations with varied excitation time since this can be easily implemented in the open field as well. Figure 8 shows the CNR values of all investigations from test series 1 and 2 at different excitation times. For the diagram, the CNR values of each detected defect at the corresponding excitation time are arithmetically averaged over all investigated distances to obtain a tendency for the behaviour of the CNR. Figure 8a shows the evolution of the mean CNR values of the reference data with filtering, averaged over the distances \(k\) at different excitation times. Defects 1 to 3 are detected in the reference data with filtering, while defects 5 to 7, which are located deeper below the surface, remain hidden. The averaged CNR of all defects ranges from 101 to 210, with a tendency to show a maximum CNR value at an excitation time interval of \(t_{\text{exc}}=[15...25]\) s. The existence of such a maximum shows that there is an optimal excitation time for each depth at which a defect is located.With a short excitation time, the defect stands out less from its surroundings or is not detectable at all, because the heat in the material flowing back to the surface may be too small to provide a local temperature change at the surface of the measurement object. With a longer excitation time, on the other hand, the surrounding area of the defect is also heated to such an extent that the defect is less likely to stand out from its surroundings during the cooling phase. The diameter of a defect has no direct influence on the optimum excitation duration for a given depth. In this case (i.e., at a constant depth), it only affects the contrast of the individual defect. Figure 8b shows the averaged CNR values of the pre-processed image, including the error bars as a measure of the scatter. The CNR values of the detected defects 1 to 3 are significantly higher than for the raw data. In particular, the visibility of the defects 1 and 2 is significantly increased by the application of PCA. Thus, the CNR values are between 940 and 1861, which corresponds to a factor of about 9 compared to the reference data with filtering for these two defects. The tendency from the reference data with filtering for a maximum CNR to occur at an excitation time interval of \(t_{\text{exc}}=[15...25]\) s is clearly seen for defects located about 1.5 mm below the surface. Defect 3, on the other hand, shows a less pronounced increase in CNR (around a factor of 3) and has the maximum CNR already at an excitation duration of 20 s. This phenomenon is not observable on the basis of the raw data. However, both too short and too long excitation durations lead to lower CNR values, which is consistent with the previous results. The CNR values for the defects 5 and  
6 range between 111 and 306, but so far do not show any discernible maximum in the parameters investigated. Since defect 5 and 6 are significantly located further from the surface than defects 1 to 3, and the depth has a significant influence on the defect visibility, an optimal excitation time for the corresponding depth of approx. 2.5 mm might occur outside the excitation times investigated. [PERSON] et al. [15] obtained an optimum excitation time of 25 s in their investigations on a flat GFRP plate, but for different depths. Therefore, the extent to which the optical excitation time depends on the depth of a defect requires further investigation. The studies show that for defects of different depths, there are corresponding intervals of excitation time at which the detectability of the defect is optimal.