Purpose The assembly of large component in out-field is an important part for the usage and maintenance of aircrafts, which is mostly manually accomplished at present, as the commonly used large-volume measurement systems are usually inapplicable. This paper aims to propose a novel coaxial alignment method for large aircraft component assembly using distributed monocular vision. Design/methodology/approach For each of the mating holes on the components, a monocular vision module is applied to measure the poses of holes, which together shape a distributed monocular vision system. A new unconstrained hole pose optimization model is developed considering the complicated wearing on hole edges, and it is solved by a iterative reweighted particle swarm optimization (IR-PSO) method. Based on the obtained poses of holes, a Plücker line coordinates-based method is proposed for the relative posture evaluation between the components, and the analytical solution of posture parameters is derived. The required movements for coaxial alignment are finally calculated using the kinematics model of parallel mechanism. Findings The IR-PSO method derived more accurate hole pose arguments than the state-of-the-art method under complicated wearing situation of holes, and is much more efficient due to the elimination of constraints. The accuracy of the Plücker line coordinates-based relative posture evaluation (PRPE) method is competitive with the singular value decomposition (SVD) method, but it does not rely on the corresponding of point set; thus, it is more appropriate for coaxial alignment. Practical implications An automatic coaxial alignment system (ACAS) has been developed for the assembly of a large pilotless aircraft, and a coaxial error of 0.04 mm is realized. Originality/value The IR-PSO method can be applied for pose optimization of other cylindrical object, and the analytical solution of Plücker line coordinates-based axes registration is derived for the first time.

Purpose In aircraft assembly, standard reference points with nominal coordinates are commonly applied for coordinate transformation between multiple measurement stations and the assembly coordinate system. For several reasons in practical application, these points often fail to envelop the key assembly space, which leads to large transformation uncertainty. This paper aims to analyze and further reduce the coordinate transformation uncertainty by introducing a new hybrid reference system (HRS). Design/methodology/approach Several temporary extension points without known coordinates are added to enhance the tightness between different stations, especially at the weakness area in the network, thus constituting an HRS together with the existing standard reference points. The coordinate transformation model of the HRS-based measurement network is established based on an extend Gauss–Markov model. By using the geometrical differential property and variance-covariance propagation law, the covariance matrixes in the transformation model are calculated, and the analytical solution of the uncertainties of transformation parameters are ultimately derived. The transformation uncertainty of each check points is presented by Helmert error expression. Findings The proposed analytical solution of transformation uncertainty is verified using the state-of-the-art Monte Carlo simulation method, but the solution process is simpler and the computation expenses are much less. Practical implications The HRS with three temporary extension points is practically applied to a tail boom in-site measurement for assembly. The average transformation uncertainty has been reduced by 26 per cent to less than 0.05 mm. Originality/value The hybrid coordinate transformation model is proposed for the first time. The HRS method for transformation uncertainty reduction is more economical and practical than increasing the number of standard reference points.

Intrinsic parameters in camera calibration are commonly solved with high precision using the homography matrix of space coordinates and image coordinates of a template. However, in practice the accuracy in the extraction of corner points of the calibration plate is usually affected by the lighting environment, leading to obvious fluctuation in the calibration results. This study proposes a novel self-calibration method to improve the calibration accuracy and reduce the instability of calibration results by using circular points and the RANdom SAmple consensus (RANSAC) method. The circular points for the intrinsic parameters are calculated using the cross-ratio method with a calibration plate containing nine corner points. The distance between the circular points and image of the absolute conic is defined. The threshold value of the RANSAC model is simulated by a computer. The intrinsic parameters are initially estimated using the unreliable calibrating images excluded by the RANSAC method. The definition of the threshold is based on the Sampson estimation. The maximum likelihood estimation method is performed to reestimate the intrinsic parameters and optimize the calibration result. The findings of the numerical simulations and experiments on wing-fuselage docking based on monocular vision demonstrate that the proposed method is more robust and efficient at improving the calibration accuracy than the traditional methods. The measurement error is reduced to less than 0.013 mm when the calibration algorithm is applied to actual applications such as wing-fuselage docking.

Purpose The purpose of this paper is to propose an on-line iterative compensation method combining with a feed-forward compensation method to enhance the assembly accuracy of a metrology-integrated robot system (MIRS). Design/methodology/approach By the integration of a six degrees of freedom (6DoF) measurement system (T-Mac), the robot’ movement can be tracked with real-time measurement. With the on-line measured data, the proposed iterative compensation for absolute positioning and the feed-forward compensation for relative linear motion are integrated into the assembly process to improve the assembly accuracy. Findings It is found that the MIRS exhibits good performance in both accuracy and efficiency with the application of the proposed compensation method. With the proposed assembly process, a component can be automatically aligned to the target in seconds, and the assembly error can be decreased to 0.021 mm for position and 0.008° for orientation on average. Originality/value This paper presents a 6DoF MIRS for high-precision assembly. Based on the system, a novel on-line compensation method is proposed to enhance the assembly accuracy. In this paper, the assembly accuracy and the corresponding distance parameter are given by a series of experiments as reference for assembly applications.

For optimization design of polymer extrusion dies, dimensional accuracy is critical to product quality of the extrudate. The extrusion dies used to be a regular geometrical profile, which is mostly composed by a straight line. Traditional optimization methods for extrusion die design used to have poor controllability when dealing with a curved profile. In this paper, the response surface optimization method is used to find out an optimal solution of the design of the extrusion die. Firstly, the Latin Hypercube Sampling method is used to generate the experiment samples for the design of experiments. Secondly, ANSYS Polyflow software is adopted to execute the computational fluid dynamics analysis. Thirdly, the Kriging method is used to generate the response surface. Finally, nonlinear programming by using Quadratic-Lagrangian algorithm is applied to find out the optimal solution. It is worth noting that Non-uniform Rational B-Splines (NURBS) modeling is used to optimize flow channel of an extrusion die in order to obtain a qualified extrudate. Thus, design variables for the optimization involve control points of the NURBS curve of the inlet cross-section. Meanwhile, two new objective functions, including minimization of point displacement and minimization of dimensional tolerance are proposed in the optimization process. Compared with existing objective functions of flow balancing and homogeneous die swell, the new objective functions of minimization of point displacement and minimization of dimensional tolerance have significant advantages of strong adaptability, more precise shape of the extrudate and fast convergence, which significantly improve efficiency of the optimization design and thus lower manufacturing costs of the extrusion die.

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