# The Automatic Algorithm of Optimizing the Position of Structured Light Sensors
## 3 Simulation  
The simulation is verified for the turbine blade body of the airplane, which is shown in Figure 4. The following approximation was used: the projector was considered a point light source, and the surface of the object was considered a complete specular reflection. Based on the light from the projector, the characteristics of the surface of the object under test, and the pointing of the camera, the possible specular reflection areas in a set of sensors are predicted. The relevant parameters optimized by the simulation are shown in Table 1. The hardware processor used in this simulation is the Intel (R) Core (TM) i5-4590 CPU @ 3.30 GHz; the Windows version used is Windows 10 Professional Edition; the simulation software used is Matlab R2022a; and the verification software used is 3 Dmax 2020. Based on these parameters and the 3D data of the object, specular reflection region prediction is performed. The performance of the sensor combination is also evaluated through simulation verification. This helps to optimize the sensor configuration, enabling accurate measurement data to be obtained for 3D structured light measurements, as well as providing strong support for the analysis and design of the turbine blade body. The optimal sensor set coverage obtained after sensor system optimization is shown below:  
Figure 9 shows the optimization results of the algorithm and the validation of the specular reflection area. There are three images in Figure 9a1-a3, and the result of sensor optimization is that only three pairs of sensors are needed to cover the measurement surface at once. The black areas in Figure 9a1-a3, represent the covered areas of the three sets of sensors. The red area is the specular reflection area. Due to the small specular reflection areas in Figure 9a1,a3, we used a red circle to indicate the specular reflection area. By comparing the red areas in the three photos, it can be seen that the specular reflection areas within the coverage areas of the three sets of sensors are different. By comparing the black areas, it can be seen that there is overlap in the coverage areas of the three sets of sensors. By comparing the red and black parts, it can be seen that the specular reflection area of  
the measurement surface of the object. Therefore, from the overall perspective of the three sets of sensors, the problem of specular reflection has been solved, and Figure 9b1-b3 is a specular reflection area validation by 3 Dmax. The highlighted white areas in Figure 9b1-b3 are the specular reflection areas calculated by 3 Dmax. By comparing the results of groups Figure 9b1-b3,c1-c3, it can be verified that the specular reflection area calculated by the optimization algorithm is accurate. Hence, it also proves that the sensors optimized by the optimization algorithm can cover the measurement area while solving the specular reflection problem. Figure 10a is a schematic diagram of sensor positions optimized by the algorithm. Figure 10b is a schematic diagram of sensor positions optimized by the expert. Figure 9c1-c3 is an optimization diagram of the number and location of sensors manually selected by experts. Figure 9: Optimization results, validation, and contrast. (**a1–a3**) Optimization results of the algorithm. The red area is the specular reflection area, the blue area is the normal area, and the red circle indicates the presence of a specular reflection area. (**b1–b3**) Verification of specular reflection by 3 Dmax. (**c1–c3**) An optimization diagram of the number and location of sensors manually selected by an expert. Bright white in (**b1–b3,c1–c3**) represents the specular reflection area. Artificial intelligence generally tends to place sensors directly in front, behind, or above objects, and the algorithm can consider more sensor positions than manual labor. From the sensor coverage area in Figure 9, it can be seen that the optimization results of the algorithm are better than those of manual methods.