# Nondestructive Surface Crack Detection of Laser-Repaired Components by Laser Scanning Thermography
## 5 Discussion  
### Influence Analysis of Surface Roughness of Repair Layer  
The periodic cladding track structure formed in the LR process poses a challenge to the detection of crack defects [20; 27]. When using laser scanning thermography to detect crack defects, the cladding track structure introduces noise to the temperature field, which needs to be further discussed and analyzed. In order to study the influence of the repair layer surface roughness on the thermographic detection, taking the polished smooth surface as a reference, thermographic detection is carried out for the smooth surface and the repair layers with different process parameters. Since the thermal emissivity of smooth surface is low, and the infrared camera mainly realizes temperature measurement based on the thermal radiation, uniform black matte paint is sprayed on its surface to improve the thermal emissivity and capture the change in temperature field more clearly. Figure 19a,d and Figure 20a,d represent the 3D surface morphology of repair area 1, smooth area, repair area 2 and repair area 3, respectively. They are obtained under the 3D-Super Depth of Field Microscope (KEYENCEVHX-600 ESO) with a magnification of 200\(\times\). During laser deposition, periodic cladding track structure is formed. The fluctuation amplitude of surface height in repair area 1, smooth area, repair area 2 and repair area 3 are 104.9 \(\upmu\)m, 39.6 \(\upmu\)m, 688.9 \(\upmu\)m and 368.3 \(\upmu\)m, respectively. This reflects the surface roughness. The repair layer material is the iron-based alloy, the material with smooth surface is the 304 stainless steel. The repair layer and smooth surface are stimulated by laser scanning in four directions of 0\({}^{\circ}\), 45\({}^{\circ}\), 90\({}^{\circ}\) and 135\({}^{\circ}\). Thermal image sequences are collected by an infrared camera for further processing and analysis. Figure 19: Thermographic detection of different surface structures: (**a**) local 3D morphology of repair area 1; (**b**) combined form of temperature change field in repair area 1; (**c**) Prewitt edge detection results for temperature change field in the repair area 1; (**d**) local 3D morphology of smooth area; (**e**) combined form of temperature change field with smooth area after mask treatment; (**f**) Prewitt edge detection for temperature change field in smooth areas. In the processing of thermal images, the temperature change fields excited by laser in four directions of 0\({}^{\circ}\), 45\({}^{\circ}\), 90\({}^{\circ}\) and 135\({}^{\circ}\) are averaged to obtain the combined form of temperature change field. Then, the image dilation algorithm is used to process the pixels with temperature higher than 2 \({}^{\circ}\)C in each frame of thermal images, and further obtain the surface temperature distribution formed by the cladding track structure [18]. In the temperature field shown in Figure 19e, as the specimen surface is relatively smooth, the surface temperature distribution under laser excitation is relatively uniform. As shown in Figures 19b or 20b,e, periodic cladding track structure exists in repair area 1, repair area 2 and repair area 3. Under laser excitation, the surface temperature field also presents periodic distribution, which is consistent with the cladding track structure. With the increase in surface fluctuation amplitude of repair layer, periodic temperature distribution becomes more obvious. Prewitt edge detection is used to extract the edge characteristics of the combined temperature change field and to detect the surface defects of the specimen. As shown in Figure 19c, surface cracks exist in repair area 1, and the fluctuation of cladding track is small, with the amplitude of height difference being 104.9 \(\upmu\)m. High quality crack shape and geometric distribution can be detected by laser scanning thermography. The temperature noise caused by non-uniform cladding track structure can be eliminated by global threshold segmentation, and the influence of cladding channel structure on crack detection is small.