Configuration Analysis of the ERS Points in Large-Volume Metrology System

Zhang, Jin; Yu, Cijun; Li, Jiangxiong; Ke, Yinglin

doi:10.3390/s150924397

Cited by 32 publications

(14 citation statements)

References 10 publications

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“…With the obtained 300 groups of transformation parameters, uncertainties of transformation parameters are derived by covariance calculation. The second method was the analytical method proposed by Jin et al (2015), which did not consider the deployment errors of ERS points. For the consistency of comparison, scaling coefficient was also added to their transformation model.…”

Section: Experiments and Case Studiesmentioning

confidence: 99%

“…Wang presented a method to reduce the errors of coordinate transformation by using a weighted point matching method, in which the weighting coefficients of KCPs were optimized by the particle swarm optimization algorithm according to the assembly requirements, and the uncertainty of the transformation parameters was obtained based on the generalized inverse theory(Wang et al ., 2015). To optimize the deployment of the ERS points, Jin developed an explicit model to estimate the uncertainties of transformation matrix errors in the registration process, by using the configuration matrix of ERS points (Jin et al ., 2015). Nevertheless, although these studies have derived the uncertainties of transformation parameters, there are still some deficiencies in them.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainties evaluation of coordinate transformation parameters in the large-scale measurement for aircraft assembly

Deng

Huang

2018

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Purpose For the measurement of large-scale components in aircraft assembly, the evaluation of coordinate transformation parameters between the coordinate frames of individual measurement systems to the assembly frame is an essential task, which is usually completed by registration of the enhanced reference system (ERS) points. This paper aims to propose an analytical method to evaluate the uncertainties of transformation parameters considering both the measurement error and the deployment error of ERS points. Design/methodology/approach For each measuring station, the measured coordinates of ERS points are first roughly registered to the assembly coordinate system using the singular value decomposition method. Then, a linear transformation model considering the measurement error and deployment error of ERS points is developed, and the analytical solution of transformation parameters’ uncertainties is derived. Moreover, the covariance matrix of each ERS points in the transformation evaluation is calculated based on a new uncertainty ellipsoid model and variance-covariance propagation law. Findings For the transformation of both single and multiple measuring stations, the derived uncertainties of transformation parameters by the proposed analytical method are identical to that obtained by the state-of-the-art iterative method, but the solution process is simpler, and the computation expenses are much less. Originality/value The proposed uncertainty evaluation method would be useful for in-site measurement and optimization of the configuration of ERS points in the design of fixture and large assembly field. It could also be applied to other registration applications with errors on both sides of registration points.

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Section: Experiments and Case Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uncertainties evaluation of coordinate transformation parameters in the large-scale measurement for aircraft assembly

Deng

Huang

2018

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“…e influence of aircraft coordinate on the docking error was analyzed by Jin et al [18]. His research focus on different arrangement forms of datum points leads to different matching accuracies.…”

Section: Introductionmentioning

confidence: 99%

Accuracy Improvement Calibrations for the Double-Position 4-PPPS Aircraft Docking System

Tang

Zhang

2020

Mathematical Problems in Engineering

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A double-positions 4-PPPS parallel mechanism is used for the aircraft fuselage assembly process to improve the docking efficiency and reduce the labor intensity. However, the accuracy is hard to guarantee, for the mechanism is large and redundant and has manufacturing and assembly errors. To improve the accuracy of the 4-PPPS parallel aircraft fuselage docking system, firstly, an averaging iteration method is proposed to calibrate the datum points in the airplane coordinate which are the references of the entire docking system. And secondly, a kinematic calibration method based on the derivative of the spatial pose transformation is proposed to calibrate up to 42 kinematic parameters. By these two methods, the final maximum position error reduced from 2.2 mm to 0.035 mm and the maximum pointing error reduced from 0.08 degree to 0.018 degree. The accuracy measurement and docking experiment prove the efficiency of the proposed methods.

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“…However, as the computation expense of MC simulation is much larger than the analytical methods (Wen et al ., 2013), the process efficiency is restricted for in-site uncertainty analysis and optimization. Most recently, Jin derived an explicit model to estimate the uncertainties of the transformation matrix errors, and the transformation uncertainty was reduced by optimizing the deployment locations of SRPs (Jin et al , 2015). However, in the real measurement situation, this approach would not be completely effective to reduce the transformation uncertainty for several reasons.…”

Section: Introductionmentioning

confidence: 99%

Coordinate transformation uncertainty analysis and reduction using hybrid reference system for aircraft assembly

Deng

Huang

2018

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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.

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Configuration Analysis of the ERS Points in Large-Volume Metrology System

Cited by 32 publications

References 10 publications

Uncertainties evaluation of coordinate transformation parameters in the large-scale measurement for aircraft assembly

Uncertainties evaluation of coordinate transformation parameters in the large-scale measurement for aircraft assembly

Accuracy Improvement Calibrations for the Double-Position 4-PPPS Aircraft Docking System

Coordinate transformation uncertainty analysis and reduction using hybrid reference system for aircraft assembly

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