# Morphological Reconstruction for Variable Wing Leading Edge Based on the Node Curvature Vectors
## 5 Conclusions  
To meet the self-perception requirements of the variable wing leading-edge morphology based on biomimetic principles, a morphological reconstruction method for the variable wing leading edge was proposed in this study, based on the relationship model between the strain and surface curvature function and the solution of segment node curvature vectors. The main work carried out is summarized as follows:  
1. The surface angle was introduced into the relationship model between strain and surface curvature to improve the accuracy of the curvature calculation for sensing points on the wing leading edge.
2. A method for solving node curvature vectors based on high-order curvature fitting functions was proposed. Compared with the conventional curvature recursion method based on first-order interpolation functions, the error in curvature field reconstruction could be reduced from 25.09% to 6.32%. Furthermore, after obtaining the curvature field of the wing leading edge, its application in the strain-surface curvature function enabled the inverse reconstruction of the strain field of the wing leading edge.
3. An optimization method for the number of sensing points based on the particle swarm algorithm was proposed, determining the optimal number of virtual sensing points. This not only simplified the complexity of the wing leading-edge sensing network but also improved the accuracy of morphological reconstruction. The results showed that, compared with the conventional curvature recursion method, the morphological reconstruction error of the wing leading edge decreased from 17.05% to 4.92%.  
The proposed method was unaffected by modeling accuracy and did not require consideration of structural material parameters and external load information. It could reconstruct approximate global measured information of the variable wing leading-edge curvature field, strain field, and displacement distribution, thereby providing real-time data support for the adaptive closed-loop control and structural health monitoring of variable wings based on biomimetic principles.  
**Author Contributions:** Formal analysis, Q.Z.; funding acquisition, J.Z.; investigation, Y.Z.; methodology, Z.W.; project administration, Y.Y.; resources, Q.W.; validation, J.C. and Z.W.; writing--original  
Figure 17: Propagation reconstruction effect comparison of LI-CPM and NCV-CPM: (**a**) relative error under 12\({}^{\circ}\) deflection angle of leading edge; (**b**) root mean square error under four leading-edge deflection angles.  
draft, Q.Z.; writing--review and editing, J.Z. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Natural Science Foundation of China (Grant Nos. 52275536, 62273179), the Fund of Aeronautics Science (Grant No. 20220028052002), the National Key Research and Development Program of the Ministry of Science and Technology (Grant No. 2021 YFC2802300), and the National Key Laboratory of Helicopter Rotor Dynamics Fund project (Grant No. 61422202207).  
Not applicable.  
The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflicts of interest.