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Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

With the improvement of modern aircraft requirements for safety, long life and economy, higher quality aircraft assembly is needed. However, due to the manufacturing and assembly errors of the posture adjustment mechanism (PAM) used in the digital assembly of aircraft large component (ALC), the posture alignment accuracy of ALC is difficult to be guaranteed, and the posture adjustment stress is easy to be generated. Aiming at these problems, this paper aims to propose a calibration method of redundant actuated parallel mechanism (RAPM) for posture adjustment.

First, the kinematics model of the PAM is established, and the influence of the coupling relationship between the axes of the numerical control locators (NCL) is analyzed. Second, the calibration method based on force closed-loop feedback is used to calibrate each branch chain (BC) of the PAM, and the solution of kinematic parameters is optimized by Random Sample Consensus (RANSAC). Third, the uncertainty of kinematic calibration is analyzed by Monte Carlo method. Finally, a simulated posture adjustment system was built to calibrate the kinematics parameters of PAM, and the posture adjustment experiment was carried out according to the calibration results.

The experiment results show that the proposed calibration method can significantly improve the posture adjustment accuracy and greatly reduce the posture adjustment stress.

In this paper, a calibration method based on force feedback is proposed to avoid the deformation of NCL and bracket caused by redundant driving during the calibration process, and RANSAC method is used to reduce the influence of large random error on the calibration accuracy.

Posture adjustment plays an important role in spacecraft manufacturing. The traditional posture adjustment method, which has a large workload and is difficult to guarantee the quality of posture adjustment, cannot meet the requirements of modern spacecraft manufacturing. This paper aims to optimize the trajectory of posture adjustment, reduce the internal force of the posture adjustment mechanism and improve the accuracy of the system.

First, the measuring point is measured by a laser tracker and the position and posture of the cabin is solved. Then, Newton–Euler method is used to construct the dynamic model of the posture adjustment system (PAS) without internal force. Finally, the adjustment time is optimized based on Fibonacci search method and the trajectory of the cabin is fitted by the fifth order polynomial.

The simulation results show that, compared with the other trajectory planning methods, this method can effectively avoid the internal force of posture adjustment caused by redundant driving, and the trajectory of velocity and acceleration obtained are continuous, meeting the engineering constraints.

In this paper, a dynamic model of PAS without internal force is constructed. The trajectory planning of posture adjustment based on this model can improve the quality of cabin assembly.

Large size of aircraft assembly tooling structure and complex measurement environment exist. The laid enhanced reference points (ERS) are subject to a combination of nonuniform temperature fields and measurement errors, resulting in increased measurement registration errors. In view of the nonuniform temperature field and measurement errors affecting the ERS point registration problem, the purpose of this paper is to propose a neural network-based ERS point registration compensation method for large-size measurement fields under a nonuniform temperature field.

The approach is to collect ERS point information and temperature data, normalize the collected data to complete the data structure design and complete the construction of the neural network prediction model by data training. The data learning is performed to complete the prediction model construction, and the prediction model is used to complete the compensation analysis of ERS points. Finally, the algorithm is verified through experiments and engineering practice.

Experimental results show that the proposed neural network-based ERS point prediction and compensation method for nonuniform temperature fields effectively predicts ERS point deformation under nonuniform temperature fields compared with the conventional method. After the compensation analysis, the registration error is effectively reduced to improve registration accuracy. Reducing the combined effect of environmental nonuniform temperature field and measurement error has apparent advantages.

The method reduces the registration error caused by combining a nonuniform temperature field and measurement error. It can be used for aircraft assembly site prediction and registration error compensation analysis, which is essential to improve measurement accuracy further.

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.

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.

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.

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.

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.

The measurement of aircraft barycenter is a verification of theoretical barycenter and is an important step of aircraft development. In the traditional measurement method of aircraft barycenter, the posture of the aircraft needs to be adjusted manually and is measured by optical instruments. The efficiency of posture adjustment depends on the proficiency of workers, and the accuracy of measurement is not high. In view of these problems of the current barycenter measurement method, this paper aims to propose an aircraft barycenter measurement method based on multi-posture.

In this method, the numerical control locator is used as a supporting part to fix and adjust the aircraft, and the calculation model of aircraft barycenter is established according to the principle of rigid body rotation and the principle of moment balance. Then, the influence of the main error sources on the measurement accuracy of aircraft barycenter is analyzed by Monte Carlo simulation, and the measurement accuracy is compared with that of the barycenter measurement method based on horizontal posture. Finally, the experiment platform of barycenter measurement was built in the laboratory and the experiments were carried out.

The experimental results show that the barycenter measurement method proposed in this paper has obvious advantages in measurement accuracy and efficiency compared with the traditional method.

This method can be used to measure the barycenter of different types of aircraft quickly and automatically.

Aircraft assembly is the crucial part of aircraft manufacturing, and to meet the high-precision and high-efficiency requirements, cooperative measurement consisting of multiple measurement instruments and automatic assisted devices is being adopted. To achieve the complete data of all assembly features, measurement devices need to be placed at different positions, and the flexible and efficient transfer relies on Automated Guided Vehicles (AGVs) and robots in the large-size space and close range. This paper aims to improve the automatic station transfer in accuracy and flexibility.

A transferring system with Light Detection and Ranging (LiDAR) and markers is established. The map coupling for navigation is optimized. Markers are distributed according to the accumulated uncertainties. The path planning method applied to the collaborative measurement is proposed for better accuracy. The motion planning method is optimized for better positioning accuracy.

A transferring system is constructed and the system is verified in the laboratory. Experimental results show that the proposed system effectively improves positioning accuracy and efficiency, which improves the station transfer for the cooperative measurement.

A Transferring system for collaborative measurement is proposed. The optimized navigation method extends the application of visual markers. With this system, AGV is capable of the cooperative measurement of large aircraft structural parts.

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).

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.

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.

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.

The purpose of this paper is to propose an assembly coordination modelling approach based on measured data for assembly quality control of multi-constrained objects in aircraft assembly. This approach aims to establish a high-precision digital mirror of physical assembly system in the virtual environment, with which the assembly process in the virtual environment can be performed synchronously with that in the physical world.

This paper presents a realistic geometrical representation model based on measured point cloud, as well as the multiple constraints modelling methods for local and global constraints with the proposed representation model. For the assembly target optimization, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, where the particle swarm optimization and simulated annealing algorithm are combined to calculate the optimal solutions.

As shown in the validation results, the minimum easiness value for easiness model in global optimization is 3.01, while the best value for weighting model by adjusting weights for more than 10 times is 1.94. The results verify that the proposed coordination modelling approach is effective to the assembly of multi-constrained objects, and the optimization model has an obvious advantage over the traditional weighting method.

This paper provides a new idea for the fine control of assembly quality of non-ideal components by introducing the measured data into the on-line assembly process. Besides, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, which overcomes the problem of traditional weighting model wherein the weightings are difficult to determine.

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).

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.

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.

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.

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.