Mr. Dongming Yan Profile

Dongming Yan

at Changchun Univ of Science and Technology

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Publications (3)

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Proceedings Article | 30 April 2024 Paper

3D imaging sensing and prediction technology of large component surface with multi-source sensing

Jing Sun, Lijuan Li, Xuezhu Lin, Lili Guo, Yue Liu, Dongming Yan

Proceedings Volume 13157, 131570S (2024) https://doi.org/10.1117/12.3017779

KEYWORDS: Deformation, Optical fibers, Optical sensing, Structured light, Optical surfaces, Data modeling, Point clouds, 3D surface sensing, Sensing systems

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In order to solve the problem that the surface deformation of large components cannot be photographed in real time due to the influence of assembly stress during assembly, a multi-source sensor surface deformation sensing and 3D imaging prediction technology for large components is proposed, which combined laser tracking, structured light detection and optical fiber sensing monitoring. Firstly, the multi-source sensor system is analyzed, and the multi-source sensor fusion sensing field is constructed. Secondly, the unified model of heterogeneous data is established to complete the accurate conversion of optical fiber monitoring wavelength to space point coordinates. Thirdly, multi-source data fusion is realized based on Gaussian process fusion algorithm to complete 3D imaging prediction of component surface deformation. Finally, a large skin component is taken as an example to simulate the assembly deformation experiment. The results show that the root-mean-square error is less than 0.1mm compared with the actual results. Based on the measured data of structured light scanning and multi-source sensing technology, a real-time sensing and prediction method for surface deformation imaging of large components is proposed. This method not only simplifies the scanning mode of structured light, but also provides a new idea for dynamic model building.

Proceedings Article | 9 January 2023 Paper

Surface deformation technology of large-scale complex components based on Laplace

Yue Liu, Dongming Yan, Xiaobo Cheng, Lijuan Li, Xuezhu Lin, Lili Guo

Proceedings Volume 12507, 125071K (2023) https://doi.org/10.1117/12.2655822

KEYWORDS: 3D modeling, Data modeling, Visual process modeling, 3D metrology, Instrument modeling, Skin, Reconstruction algorithms

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In this paper, based on the Laplace deformation technique of differential coordinates, a surface deformation technique of large-scale complex components based on optimal control points is proposed. Firstly, according to the structural characteristics and constraint conditions of the members, the force and deformation trend of the model are analyzed. The force on the curved surface is simplified into a simply supported beam section for force analysis. The deflection curve trend of the members under different constraint conditions is qualitatively analyzed. The control points are arranged at the maximum deformation to ensure the consistency of the maximum shape variables; Secondly, the arrangement of control points of components is optimized according to the deflection curve, and the points are collected in proportion along the direction of the deflection curve at a certain distance. After multiple deformation superimposition, the spacing and position distribution of control points are continuously optimized; Then, based on the centroid, the mapping relationship between the control points of the source model and the control points measured after deformation is established, and the corresponding positions of the corresponding points on the original model and the deformed model are determined; Finally, the Laplace deformation of the surface is carried out through experiments to realize the surface reconstruction. The results show that the accuracy of surface reconstruction can be controlled within 0.15mm, which overcomes the limitation of traditional large-scale deformation, greatly shortens the time and improves the actual operation level.

Proceedings Article | 9 January 2023 Paper

Research on large-scale measurement field deployment technology based on FBI algorithm

Dongming Yan, Lijuan Li, Yue Liu, Xuezhu Lin, Lili Guo

Proceedings Volume 12507, 125070H (2023) https://doi.org/10.1117/12.2654156

KEYWORDS: Clouds, Optimization (mathematics), Laser applications, Data conversion, Visibility

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With the advent of the "Industry 4.0" era, the requirements for measurement efficiency, size and accuracy in the assembly process of large-scale equipment have been continuously improved. In the assembly process of large-scale equipment, due to the limitations and occlusions of components and assembly tooling, a single laser tracker cannot complete the measurement of all target points. Therefore, it is necessary to use multiple trackers to work together to build a measurement network covering the entire assembly space. In this paper, through the forensic-based investigation optimization algorithm, the three-dimensional coordinates of the stations of multiple laser trackers are used as the high-dimensional input parameters, the side of the bounding box of the large-scale measurement field is used as the feasible region of the high dimensional parameters, the ray accessibility of the laser tracker is used as the statistical result, the number of public transit points of adjacent stations of the laser tracker and the number of visible digital-analog key points are used as constraints, the ratio of the number of visible points of multiple laser trackers to the total number of points is used as the objective function, the optimization is carried out in the form of greedy iterative fitness function, and finally the maximum coverage rate under the measurement network is obtained in complex environments such as tooling occlusion. In a word, this method shortens the station layout time and the overall assembly period through autonomous calculation, and has certain practical significance for improving the assembly efficiency of large-scale equipment.

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