## 5 Conclusions  
In this paper, the following conclusions are obtained to improve the accuracy of the bending angle of steel bars:  
1. The mechanism of steel bar bending and forming was studied, and the effects of support shaft diameter, bending shaft diameter, and bending shaft rotation radius on steel bar springback angle were analyzed by ANSYS explicit dynamics simulation and field experiments, and then the bending structure parameters were optimized by orthogonal test method, and finally the structural parameters were 20 mm support shaft diameter, 40 mm bending shaft diameter, and 80 mm bending shaft rotation radius, which could effectively reduce the steel bar springback angle and improve the accuracy of the steel bar bending angle after bending. 2. This article innovatively proposed the cubic spline interpolation method to solve the compensation formula for the steel bar bending springback angle. The accuracy of the springback angle compensation formula obtained by the least squares linear fitting method, Newton interpolation polynomial method, and cubic spline interpolation method was compared. The results show that the cubic spline interpolation method has high fitting curve accuracy and can effectively improve the accuracy of the steel bar bending angle. 3. This article focuses on parameter analysis and optimization of the bending mechanism of the steel bar bending machine, and the research has limitations. Different bending \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Bending Angle (\({}^{\circ}\))** & **30** & **45** & **90** & **135** & **150** \\ \hline Least square linear fitting (\({}^{\circ}\)) & \(-0.34\) & \(-0.19\) & \(+0.33\) & \(+0.03\) & \(-0.09\) \\ Least squares square fitting (\({}^{\circ}\)) & \(-0.12\) & \(-0.15\) & \(+0.10\) & \(-0.07\) & \(-0.05\) \\ Newton interpolation polynomial fitting (\({}^{\circ}\)) & \(+0.08\) & \(-0.02\) & \(+0.06\) & \(-0.02\) & \(+0.13\) \\ Cubic spline interpolation fitting (\({}^{\circ}\)) & \(+0.08\) & \(-0.01\) & \(+0.06\) & \(+0.01\) & \(+0.03\) \\ Actual springback angle (\({}^{\circ}\)) & \(6.82\) & \(6.41\) & \(5.11\) & \(4.63\) & \(4.49\) \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Parameter error table of springback angle of different fitting curves. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Bending Angle (\({}^{\circ}\))** & **30** & **45** & **90** & **135** & **150** \\ \hline Least square linear fitting (\({}^{\circ}\)) & \(-0.34\) & \(-0.19\) & \(+0.33\) & \(+0.03\) & \(-0.09\) \\ Least squares square fitting (\({}^{\circ}\)) & \(-0.12\) & \(-0.15\) & \(+0.10\) & \(-0.07\) & \(-0.05\) \\ Newton interpolation polynomial fitting (\({}^{\circ}\)) & \(+0.08\) & \(-0.02\) & \(+0.06\) & \(-0.02\) & \(+0.13\) \\ Cubic spline interpolation fitting (\({}^{\circ}\)) & \(+0.08\) & \(-0.01\) & \(+0.06\) & \(+0.01\) & \(+0.03\) \\ Actual springback angle (\({}^{\circ}\)) & \(6.82\) & \(6.41\) & \(5.11\) & \(4.63\) & \(4.49\) \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Table of springback angle parameters of different fitting curves. mechanism structures and processed steel bar diameters can have an impact on the springback angle, so this springback compensation formula is only applicable to the current structure and 10 mm steel bar bending processing. Subsequent research needs to take into account the actual situation, taking into account the structural parameters and steel bar diameter and using the cubic spline interpolation method to solve the springback compensation formula. * In view of the problem of steel bar bending and springback, follow-up research can consider using deep learning methods to build a model to train the springback angle data in order to achieve independent control and automatic compensation of the springback angle, improve the accuracy of the steel bar bending angle, and realize intelligent rebar processing. J.R.: Formal analysis, Funding acquisition, Investigation, Methodology, Formal analysis, Supervision and Writing--review and editing. J.W.