Online Adaptive Method for Obtaining High- Precision Spherical Joint Positions With the Lower Internal Force Assembly of Large-Scale Aircraft Components

The high-quality assembly of large-scale aircraft components (LACs) is crucial for modern aircraft manufacturing. The spherical joints are important parts connecting the numerical control locators (NCLs) and LAC. Nevertheless, determining the position of spherical joint centers (SJCs) is challenging because more than half of the ball heads are wrapped inside the ball sockets. Furthermore, the multiaxis asynchronous motion of NCLs will cause internal forces during the posture adjustment process, reducing assembly quality. Hence, an online adaptive scheme with lower internal forces is proposed to obtain the high-precision SJC positions. First, an innovative mathematical model for determining SJC positions with a Jacobian matrix is constructed, and a high-precision solution is achieved via the adaptive estimation Jacobian matrix method, transforming problems that cannot be directly measured into computable solutions. Second, a multiaxis synchronization error is introduced and its mapping relationship with posture-coupled error is established to ensure coordinated NCL motion and reduce internal forces. Finally, the effectiveness of the proposed method is demonstrated through experiments. The maximum error for SJC positions is 0.19 mm, a notable improvement from 0.4 mm. By introducing synchronization error, the internal force is decreased by at least 54%, and its fluctuation range by 54.9%, thereby ensuring assembly quality. This study provides a new method for improving aircraft assembly quality.

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Publication Details

Journal
IEEE Transactions on Industrial Informatics
Published
2024-12-03
DOI
https://doi.org/10.1109/tii.2024.3495764
Citations
2
Primary Topic
Engineering Technology and Methodologies
Type
article
Field-Weighted Citation Impact
0.70

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article

Online Adaptive Method for Obtaining High- Precision Spherical Joint Positions With the Lower Internal Force Assembly of Large-Scale Aircraft Components

Qihang Chen, Runze Liu, Hu Lu, Yajun Li et al.
2 citations
IEEE Transactions on Industrial Informatics
Engineering Technology and Methodologies
0.70
article

Online Adaptive Method for Obtaining High- Precision Spherical Joint Positions With the Lower Internal Force Assembly of Large-Scale Aircraft Components

Qihang Chen, Runze Liu, Hu Lu, Yajun Li, Wei Liu, Changyong Gao, Yang Zhang
article en
2 citations

Abstract

The high-quality assembly of large-scale aircraft components (LACs) is crucial for modern aircraft manufacturing. The spherical joints are important parts connecting the numerical control locators (NCLs) and LAC. Nevertheless, determining the position of spherical joint centers (SJCs) is challenging because more than half of the ball heads are wrapped inside the ball sockets. Furthermore, the multiaxis asynchronous motion of NCLs will cause internal forces during the posture adjustment process, reducing assembly quality. Hence, an online adaptive scheme with lower internal forces is proposed to obtain the high-precision SJC positions. First, an innovative mathematical model for determining SJC positions with a Jacobian matrix is constructed, and a high-precision solution is achieved via the adaptive estimation Jacobian matrix method, transforming problems that cannot be directly measured into computable solutions. Second, a multiaxis synchronization error is introduced and its mapping relationship with posture-coupled error is established to ensure coordinated NCL motion and reduce internal forces. Finally, the effectiveness of the proposed method is demonstrated through experiments. The maximum error for SJC positions is 0.19 mm, a notable improvement from 0.4 mm. By introducing synchronization error, the internal force is decreased by at least 54%, and its fluctuation range by 54.9%, thereby ensuring assembly quality. This study provides a new method for improving aircraft assembly quality.

IEEE Transactions on Industrial InformaticsVol. 21(3)
Commercial Aircraft Corporation of China (China) (CN), Dalian University of Technology (CN)
National Natural Science Foundation of China, Liaoning Revitalization Talents Program
Openalex Percentile: Top 24%
Engineering Technology and Methodologies
0.70
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