Combined Measurement Based Wing-Fuselage Assembly Coordination via Multiconstraint Optimization

In the field of aircraft manufacturing, the demand for high aerodynamic performance and long fatigue life is growing. This makes the high-precision assembly of large components and assembly coordination increasingly important. This is particularly prominent for wing-fuselage joining due to the large size, measurement difficulty, and multiconstraint coordination. In this article, we propose a novel optimization method for the wing-fuselage assembly coordination problem, as well as an assembly gap measurement approach. First, a gap measurement framework combining a laser tracker, 3-D scanner, and photogrammetry is adopted to solve the occlusion problem that makes measurement difficult in traditional methods. Compatible tooling is utilized to transform the scanned point cloud data in the local coordinate system to the global aircraft assembly coordinate system. Based on this, a comprehensive wing-fuselage pose coordination model is then established, which takes engineering constraints into account to realize assembly gap redistribution for wing-fuselage joining. The transformation parameters of pose adjustment are solved by the proposed multiconstraint optimization algorithm based on the Gauss-Newton method. Finally, experiments on synthetic data and actual data have verified the effectiveness of the coordination method. Results show that our method significantly optimizes the gap distribution within the given tolerance and outperforms traditional methods in both accuracy and efficiency. With advantages of high efficiency and accuracy, our method can be well applied to the wing-fuselage joining and satisfy the requirement of the large component assembly.