## 7 Experiment  
The cutter position points obtained by the tool path planning algorithm are further processed by the post-processing algorithm to calculate the corresponding displacement data and driving speed data of each axis. Finally, the driving data are integrated into a machining file and imported into the motion control system of the symmetrical XYZ-3 RPS double-sided hybrid machine tool. Single-sided machining and double-sided collaborative machining experiments were conducted on nylon material workpieces (350 \(\times\) 200 \(\times\) 50) using a 3 mm ball nose end mill, with an axial depth of 2 mm and the same machining tool path. As shown in Figure 3, the machine tool is divided into left and right sides, and partial double-sided collaborative driving data on the left side are shown in Tables 2 and 3. \(x,\,y,\,z,\,d_{1},\,d_{2},\,d_{3}\) represent the driving displacement of the six driving screws of the XYZ-3 RPS hybrid machine tool on the left side, while \(v_{x},\,v_{y},\,v_{z},\,v_{1},\,v_{2},\,v_{3}\) represent the driving speed of the six driving screws of the XYZ-3 RPS hybrid machine tool on the left side. The double-sided collaborative machining process of propeller blades is shown in Figure 9.  
Figure 8: The sigmoid deformation curve. Through the analysis of curve data, the comparison data of evaluation indicators can be obtained as shown in Table 4. It can be concluded that the deformation range of single-sided machining is between \(-\)0.209-0.456 mm, and the deformation range of double-sided collaborative machining is between \(-\)0.193-0.138 mm. By comparing the deformation range results, it can be seen that the double-sided collaborative machining method to some extent weakens the local influence of overturning torque and torsional torque on workpiece deformation during single-sided machining. Especially during each cycle of machining back and forth, the problem of machining deformation is effectively improved. However, the uneven force distribution on both sides of the machining area and the deformation resilience can still lead to significant deformation from the perspective of the entire machining process. Therefore, the process parameters of the double-sided collaborative machining method still need to be optimized in subsequent research. \(X_{p}\), \(PP\), \(rms\), and \(CL\) represent the peak value of vibration, the peak-to-peak value of vibration, the root mean square value of vibration, and margin indicators, respectively. The vibration peak value and peak-to-peak value reflect the amplitude and range of the variation curve. The root mean square value of vibration reflects the strength and stability of the vibration signal. If this indicator abnormally increases, it indicates that there are hidden dangers in the processing process. The margin indicator is the ratio of vibration peak to square root amplitude, reflecting the impact characteristics of the vibration signal. The larger the indicator, the stronger the processing vibration impact. By comparing the evaluation indicators, it can be seen that double-sided collaborative machining has greatly improved the vibration compared to unsupported single-sided machining, indicating that the double-sided collaborative machining method can improve the machining result effectively. Finally, the quality of the machined blade is evaluated in the experiment by measuring the blade radius, section length under three radii, and surface roughness. Measure the blade radius length R and the section length at 0.2R, 0.5R, and 0.95R using the range finder, and take the average of three times as the final result, as shown in Table 5. The deviation rate of blade radius is 0.13%, which meets the requirement of \(\pm\)0.2% for extreme radius tolerance of Class S in ISO 484-2:2015 [19]. The deviation rates of section length are 0.38%, 0.46%, and 0.35%, respectively, meeting the requirement of +2% for blade section length tolerance of Class S in ISO 484-2:2015 [19].