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Quality inspection and error correction of fork-ear type wing-fuselage docking assembly based on multi-camera stereo vision

Published online by Cambridge University Press:  03 December 2024

Y.G. Zhu Open the ORCID record for Y.G. Zhu [Opens in a new window] ,
D. Li ,
Y. Wan ,
Y.F. Wang Open the ORCID record for Y.F. Wang [Opens in a new window] ,
Z.Z. Bai  and
W. Cui Open the ORCID record for W. Cui [Opens in a new window]
Y.G. Zhu*
Affiliation:
Department of Aeronautical Manufacturing and Mechanical Engineering, Nanchang HangKong University, Nanchang, China
D. Li
Affiliation:
Department of Aeronautical Manufacturing and Mechanical Engineering, Nanchang HangKong University, Nanchang, China
Y. Wan
Affiliation:
Department of Aeronautical Manufacturing and Mechanical Engineering, Nanchang HangKong University, Nanchang, China
Y.F. Wang
Affiliation:
Department of Aeronautical Manufacturing and Mechanical Engineering, Nanchang HangKong University, Nanchang, China
Z.Z. Bai
Affiliation:
AVIC Shanxi Aircraft Industry Corporation LTD, Hanzhong, China
W. Cui
Affiliation:
Department of Aeronautical Manufacturing and Mechanical Engineering, Nanchang HangKong University, Nanchang, China
*
Corresponding author: Y.G. Zhu; Email: [email protected]
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Abstract

During the automatic docking assembly of aircraft wing-fuselage, using monocular camera or dual-camera to monitor the docking stage of the fork-ear will result in an incomplete identification of the fork-ear pose-position and an inaccurate description of the deviation in the intersection holes’ position coordinates. To address this, a quality inspection and error correction method is proposed for the fork-ear docking assembly based on multi-camera stereo vision. Initially, a multi-camera stereo vision detection system is established to inspect the quality of fork-ear docking assembly. Subsequently, a spatial position solution mathematical model of the fork-ear feature points is developed, and a spatial pose determination mathematical model of fork-ear is established by utilised the elliptical cone. Finally, an enhanced artificial fish swarm particle filter algorithm is proposed to track and estimate the coordinate of the fork-ear feature points. An adaptive weighted fusion algorithm is employed to fuse the detection data from the multi-camera and the laser tracker, and a wing pose-position fine-tuning error correction model is constructed. Experimental results demonstrate that the method enhances the effect of the assembly quality inspection and effectively improves the wing-fuselage docking assembly accuracy of the fork-ear type aircraft.

Keywords

wingfuselageassemblyfork-earstereo vision
Type
Research Article
Information
The Aeronautical Journal , Volume 129 , Issue 1334 , April 2025 , pp. 1054 - 1076
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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