We investigate and analyze the transmission performance of free-space optical (FSO) communication systems at three different working wavelengths, 1.55, 4, and 9 μm, under the combined effects of weather conditions (rain, snow, fog, and haze) and atmospheric turbulence, which is modeled by the gamma-gamma turbulence model. The simulation system of FSO communication based on quadrature phase-shift keying (QPSK) modulation format with a data transmission rate of 10 Gbps is built using OptiSystem software. The results show that the working wavelength has less influence on the transmission performance of the FSO communication system under rainy weather and turbulence conditions. In snowy and turbulent conditions, the short-wavelength laser has a stronger transmission advantage. In fog and turbulence situations, the transmission performance of the FSO communication system is significantly improved with the increase of wavelength. Under the combined influence conditions of haze and medium turbulence, the transmission distance of 9-μm laser is 2.67 and 1.56 times that of 1.55- and 4-μm lasers, respectively, when the bit error rate is 10−9. The results can provide an important reference for the design and optimization of practical FSO communication systems.
KEYWORDS: Deformation, Optical fibers, Optical sensing, Structured light, Optical surfaces, Data modeling, Point clouds, 3D surface sensing, Sensing systems
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.
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.
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.
In order to ensure the assembly precision in the digital assembly process of large workpiece and reduce the assembly error caused by the standard point coordinate offset caused by surface deformation, an irregular surface workpiece strain field monitoring system based on FBG sensing array was designed. The system tests the surface deformation of the workpiece with gradient features by means of an FBG array laid on the surface of the workpiece. It can calculate the micro-displacement offset of the standard point of the workpiece. The simulation results show that the strain is related to the position, size and workpiece structure of the force application. The strain field has a significant gradient change on the surface of the workpiece. In the experiment, the FBG array arrangement was completed according to the strain gradient feature distribution. Each FBG can effectively acquire the dependent variable at each point. The relationship between the amount of micro-displacement and the wavelength shift under different applied conditions is obtained. The error distribution of the micro-displacement amount is calculated. It verifies the feasibility of the system.
In this paper, the uncertainty model of laser radar and Metrascan detection is established, combined with the the accessibility of laser radar in the actual measurement, the accuracy of the measured network is simulated and analyzed, and a digital measurement method, which combines the advantages of two advanced measurement techniques, Metrascan and laser radar, is proposed. This method of netted measurement for different digital equipment, uses a high precision laser radar coordinate system as the reference transformation coordinate system, improves the measurement precision of large-size measurement of Metrascan, thus, which realizes the high precision and high efficiency measurement for the digitization of the aircraft shape.
In the process of manufacturing large components, such as aerospace, automobile and shipping industry, some important mold or stamped metal plate requires precise forming on the surface, which usually needs to be verified, if necessary, the surface needs to be corrected and reprocessed. In order to make the correction of the machined surface more convenient, this paper proposes a method based on Laser 3D projection system, this method uses the contour form of terrain contour, directly showing the deviation between the actually measured data and the theoretical mathematical model (CAD) on the measured surface. First, measure the machined surface to get the point cloud data and the formation of triangular mesh; secondly, through coordinate transformation, unify the point cloud data to the theoretical model and calculate the three-dimensional deviation, according to the sign (positive or negative) and size of the deviation, use the color deviation band to denote the deviation of three-dimensional; then, use three-dimensional contour lines to draw and represent every coordinates deviation band, creating the projection files; finally, import the projection files into the laser projector, and make the contour line projected to the processed file with 1:1 in the form of a laser beam, compare the Full-color 3D deviation map with the projection graph, then, locate and make quantitative correction to meet the processing precision requirements. It can display the trend of the machined surface deviation clearly.
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