Reflector dot matrix supporting structure design method based on topological optimization reconstruction and point cloud reconstruction

Abstract

The invention provides a reflector dot matrix supporting structure design method based on topological optimization reconstruction and point cloud reconstruction, which comprises the following steps: establishing a reflector dot matrix supporting structure topological optimization model, and outputting an STL (Standard Template Library) model of an optimal topological layout; performing automatic curved surface reconstruction on the STL point cloud, and generating a solid shell model of the support structure through offset and geometric processing; carrying out grid division on the surface of the inner cavity of the solid shell model, generating an STL model again, filling the dot matrix in the inner cavity of the shell, and simplifying the dot matrix into a beam element finite element model; extracting beam element end free nodes on an envelope contour boundary of the beam element finite element model to generate a point cloud, and performing triangularized mesh reconstruction on the point cloud; the reconstructed triangularized mesh serves as the inner boundary of the entity shell model and is assembled with the entity shell model, and a complete reflector dot matrix supporting structure finite element simulation model is generated; and carrying out simulation verification and iterative optimization on the mirror dot matrix support finite element model in an installation and adjustment state.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of space optical remote sensors, and particularly relates to a mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction, which is used for the design of a space camera mirror point array support structure with ultra-light mass, high bearing performance and high surface shape precision requirements. BACKGROUND

[0002] In order to improve the imaging quality of an optical system of a space remote sensing camera, the design of an optical mirror support structure must first ensure the stability of the position and surface shape precision of the optical mirror during the assembly and adjustment process and under on-orbit working conditions, and the weight of the optical mirror support structure needs to be as light as possible considering the launch cost. The point array support structure is composed of a sandwich structure of periodically arranged unit cells and shell panels, and has great potential in the field of space remote sensing due to its light weight, high specific stiffness, high design freedom and other advantages. The design of the point array structure is generally combined with topology optimization technology, and is realized through 3D printing manufacturing.

[0003] Traditional point array structure design usually relies on experience, is low in efficiency and lacks systematicness. Although existing three-dimensional modeling software can handle complex geometric structures, there are challenges such as insufficient model repair and insufficient precision in converting the model after topology optimization. The current structure optimization software uses the SIMP (Solid Isotropic Material with Penalization) algorithm based on gradient for topology optimization, and the boundary of the optimized topology structure is not clear enough, lacking an explicit and CAD-friendly expression form. The topology optimization result cannot be directly used for manufacturing, and needs to be manually geometrically reconstructed after design, which is difficult to edit and lacks parameter control, and is heavily dependent on the experience of designers. The complex point array structure directly used for finite element analysis has too large a calculation amount, which affects the design iteration efficiency. The connection design of the point array support structure and the shell panel relies on experience and lacks an automatic matching method. SUMMARY

[0004] In order to overcome the deficiencies in the prior art, the present inventors have made intensive research and provided a mirror point array support structure design method integrating topology optimization, automatic geometric reconstruction and point cloud reconstruction point array finite element simulation, which solves at least one of the following technical problems:

[0005] 1. The mass of the point array support structure is as light as possible;

[0006] 2. Under the assembly and adjustment state of the mirror assembly, the position change of the mirror caused by the point array support structure is as small as possible;

[0007] 3. Under the assembly and adjustment state of the mirror assembly, the surface shape error introduced by the point array support structure to the mirror surface is as small as possible;

[0008] 4. Realize the automation of support structure topology optimization geometry reconstruction, and reduce the manual intervention time as much as possible;

[0009] 5. Realize the efficient calculation of lattice structure simplification, and reduce the finite element calculation complexity as much as possible.

[0010] The technical scheme provided by the application is as follows:

[0011] In a first aspect, a mirror lattice support structure design method based on topology optimization reconstruction and point cloud reconstruction comprises:

[0012] Considering the load working condition of the mirror assembly, an initial design space model of the mirror lattice support structure is established, a topology optimization model of the mirror lattice support structure is established, and an STL model of an optimal topology layout is output;

[0013] The STL point cloud is automatically reconstructed to obtain a first closed free-form surface; the STL point cloud is inwardly offset, and after local modification, the STL point cloud is automatically reconstructed again to generate a second closed free-form surface; the two closed free-form surfaces are geometrically processed to generate a solid shell model of the support structure;

[0014] The inner cavity surface of the solid shell model is meshed and an STL model is generated again, the lattice type and cell parameters are specified for lattice filling, and the lattice is simplified into a beam element finite element model;

[0015] The beam element end free nodes on the envelope contour boundary of the beam element finite element model are extracted to generate a point cloud, and the point cloud is triangulated and meshed;

[0016] The reconstructed triangulated mesh is used as the inner boundary of the solid shell model, and the solid shell model is assembled to generate a complete mirror lattice support structure finite element simulation model;

[0017] The mirror lattice support finite element model is simulated and verified in the adjustment state and iteratively optimized, and if the simulation result does not satisfy the threshold, the lattice density or the shell structure thickness is adjusted parametrically to realize closed-loop optimization.

[0018] In a second aspect, a mirror lattice support structure design device based on topology optimization reconstruction and point cloud reconstruction comprises:

[0019] One or more processors;

[0020] A storage device for storing one or more programs,

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the mirror lattice support structure design method based on topology optimization reconstruction and point cloud reconstruction of the first aspect.

[0022] In a third aspect, a readable storage medium has a computer program stored thereon, which, when executed by a processor, implements the mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of the first aspect.

[0023] In a fourth aspect, a computer program product comprises a computer program (also referred to as code or instructions) that, when executed, performs the mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of the first aspect.

[0024] The mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction provided by the present application has the following beneficial effects:

[0025] (1) The mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction provided by the present application takes minimizing mirror rigid body displacement and mirror surface shape error as the goal, establishes a mirror point array support structure topology optimization model with volume fraction as the constraint, and realizes lightweight point array support structure, as well as the goal of minimizing the position change of the mirror under the mirror assembly adjustment state and the mirror surface shape error introduced by the mirror surface.

[0026] (2) The mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction provided by the present application uses the NURBS surface fitting algorithm to perform automatic surface reconstruction on the STL point cloud, performs an inward bias operation on the reconstructed surface, performs automatic surface reconstruction again on the biased surface, and performs solidification and Boolean operation processing on the two closed surfaces to generate a support structure solid shell model. The geometry reconstruction of the point array support structure topology optimization result realizes automation, quickly converts the STL model into a parameterized solid model, and reduces the manual modeling intervention time by more than 50%.

[0027] (3) The mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction provided by the present application performs grid division on the inner cavity surface of the solid shell model and generates an STL model again, specifies the point array type and cell parameters for point array filling, and simplifies the point array to a beam element finite element model. Compared with the solid grid, the point array structure beam element simplified model improves the calculation efficiency by more than 70%, greatly reducing the complexity of simulation calculation.

[0028] (4) The application provides a mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction, extracts beam element end free nodes on a beam element finite element model envelope contour boundary to generate point clouds, and performs triangulation grid reconstruction on the point clouds; the reconstructed triangulation grid is taken as an inner boundary of a solid shell model, and is assembled with the solid shell model to generate a complete mirror point array support structure finite element simulation model; the point cloud reconstruction technology realizes accurate matching of the point array structure and the shell structure finite element model, and improves the accuracy and rationality of the point array support structure model simulation result. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 A flowchart of the mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of the application;

[0030] Figure 2 A mirror support topology optimization design space, element density and STL model generated in an embodiment of the application;

[0031] Figure 3 A STL point cloud automatic curved surface reconstruction and solid shell generation process schematic diagram in an embodiment of the application;

[0032] Figure 4 A mirror support structure internal point array filling schematic diagram in an embodiment of the application;

[0033] Figure 5 A mirror point array structure point cloud reconstruction and finite element model generation schematic diagram in an embodiment of the application. DETAILED DESCRIPTION

[0034] The characteristics and advantages of the application will become more apparent with the following detailed description of the application.

[0035] The special word "exemplary" herein means "serving as an example, embodiment or illustrative". Any embodiment described herein as "exemplary" is not necessarily interpreted as superior or better than other embodiments.

[0036] The application provides a mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction, as shown in Figure 1 The method comprises the following steps:

[0037] I. Mirror point array support structure topology optimization and STL model generation

[0038] The initial design space model of the mirror point array support structure is constructed using software such as CAD, Creo Parametric, and the like, and based on the load working conditions of the mirror assembly (such as gravity, temperature field, forced displacement, vibration mode, and the like), a topology optimization model is established with the minimization of the rigid body displacement of the mirror and the mirror surface shape error as the target, and the volume fraction as the constraint, and the variable density method is used to iteratively solve the optimal topology layout. The optimization result is exported as an STL model, and the model surface smoothness is ensured through mesh redivision and smoothing processing.

[0039] II. Automatic surface reconstruction and solid shell model generation of STL point cloud

[0040] The digital profile editing module of CATIA is used to set reasonable filtering parameters for adaptive filtering of the STL point cloud to reduce the modeling calculation burden, the surface rapid reconstruction module is used to automatically reconstruct the surface of the STL point cloud, and through the setting of node tolerance, automatic tangent constraint, point cloud and surface fitting optimization, etc., the first closed free surface which is well fitted with the point cloud data is constructed.

[0041] The STL point cloud is inwardly offset, and local trimming (such as hole opening) is performed according to the processing and assembly process requirements, and the second closed free surface is generated by automatic surface reconstruction fitting again, and the two closed free surfaces are solidified, and the Boolean operation is performed for geometric processing to generate the solid shell model of the support structure.

[0042] III. Internal point array filling of mirror point array support structure

[0043] The internal cavity surface of the solid shell model is meshed and an STL model is generated again, which is imported into a point array structure generation software (such as Materialise 3-matic), and the point array type and cell parameters are specified for point array filling of the shell internal cavity, and the complex point array is quickly simplified into a beam element finite element model, and the equivalent stiffness matching (such as material elastic modulus, cross-sectional moment of inertia) is performed to reduce the complexity of subsequent finite element calculation.

[0044] IV. Point cloud reconstruction, point array and shell structure finite element assembly model generation

[0045] The beam element end free nodes on the envelope contour boundary of the beam element finite element model are extracted to generate a point cloud, and a greedy triangulation projection algorithm is used to triangulate the point cloud. The above point cloud reconstruction triangular mesh is used as the inner boundary of the solid shell model, and the solid shell model is assembled to generate a complete mirror point array support structure finite element simulation model.

[0046] V. Simulation verification and iterative optimization

[0047] The simulation verification and iterative optimization of the mirror lattice support finite element model in the adjustment state are carried out, and then the statics, dynamics and thermal-mechanical coupling simulation are carried out to verify the mirror surface shape precision and the structural reliability of the support structure. If the simulation result does not meet the threshold, the parameterized adjustment of the lattice density or the shell structure thickness is realized to realize closed-loop optimization.

[0048] Taking the mirror support structure of a space remote sensing camera as an example, the structural optimization design process is exemplarily described.

[0049] (1) Taking the 1.5 m aperture remote sensing camera main mirror support structure as the object, the initial design space model of the support structure is established by using Creo Parametric software, which is imported into Altair Hypermesh finite element pre-processing software and divided into regular hexahedral mesh, the mesh size is 5 mm, the boundary condition is defined as the bottom six-point fixed support, and the load case is set as the main mirror adjustment state gravity. In the Altair OptiStruct topology optimization module, the relative density (0-1) of the hexahedral mesh element of the support structure is selected as the topology optimization design variable, the maximum displacement of the mirror surface and the mirror surface shape error are defined as the objective function, the constraint condition is set as the volume fraction not more than 30% of the original volume, and the symmetry constraint and the engineering manufacturing constraint are added, the method of controlling the minimum member size is used to suppress the chessboard effect and the mesh dependence phenomenon, the SIMP topology optimization algorithm of OptiStruct is executed, and the final topology layout is obtained after 32 times of iterative optimization. The finite element model file and the shape file generated by optimization are used as input files, the OSSmooth tool is used to create the equal-density boundary surface of the topology result, the STL model is output, and if the surface quality of the output STL model does not meet the requirements, the surface quality is improved by mesh redivision and smoothing algorithm. The process is as Figure 2 shown.

[0050] (2) Import the STL model using the "Cloud Import" function of the CATIA digital profile editing module, set the unit system to millimeters; activate the "Adaptive Filter" tool, set the filter parameters to a minimum point spacing of 0.5 mm and a maximum point spacing of 2.0 mm, and perform adaptive filtering to reduce the size of the point cloud; use the "Automatic Surface" function of the surface quick reconstruction module, set the feature recognition parameter surface deviation to 0.5 mm, and use the NURBS surface fitting algorithm (3x3 order) to automatically reconstruct the filtered STL point cloud, and by setting the node tolerance, automatic tangent constraint, point cloud and surface fit optimization, etc., a first closed free-form surface is constructed which is well fitted to the point cloud data. Perform an inward offset operation on the STL point cloud, and perform local trimming, feature addition and deletion, etc. on the offset STL point cloud surface to adapt to the needs of the machining and assembly process, and then perform automatic surface reconstruction fitting again to generate a second closed free-form surface. The two closed free-form surfaces are solidified and subjected to Boolean operation processing to generate a support structure solid shell model. The process is as shown in Figure 3 .

[0051] (3) Mesh the inner surface of the solid shell model, regenerate the STL model, and import it into the Materialise 3-matic lattice structure generation software; select the lattice type as BCC lattice, specify the lattice cell parameters as 5mm x 5mm x 5mm, use the "Lightweights" module "Create Unit Graph" function to fill the surrounding area of the inner surface STL model with lattice, and then use the "Export graph mesh" function to quickly export the lattice as a beam element finite element model, and set the equivalent cross section and equivalent elastic modulus of the beam element according to the 3D printing material process. The process is as shown in Figure 4 .

[0052] (4) Extract the end nodes on the envelope contour boundary of the beam element finite element model to generate a point cloud, and use the greedy triangulation projection algorithm for 3D reconstruction; the process is as follows: project the point cloud onto a two-dimensional coordinate plane by normal projection; triangulate the projected point cloud in the plane to obtain the topological connection relationship of each point, and the plane triangulation process applies a spatial region growing algorithm based on Delaunay triangulation; determine the topological connection between each original three-dimensional point according to the topological connection relationship of the projected points in the plane, and the triangulated mesh model is obtained. Accurately match the triangular mesh generated by the above point cloud reconstruction with the inner boundary of the support shell structure to generate a complete mirror lattice support structure finite element simulation model. The process is as shown in Figure 5 .

[0053] (5) The finite element model of the mirror lattice support is simulated under the state of adjustment gravity working condition, and then statics, dynamics and thermal-mechanical coupling simulation are carried out, so as to verify the surface accuracy and structural reliability, if the simulation result does not meet the threshold, the parameterized adjustment of the lattice density or the shell thickness is carried out, so as to realize closed-loop optimization.

[0054] The application further provides a mirror lattice support structure design device based on topological optimization reconstruction and point cloud reconstruction.

[0055] One or more processors;

[0056] A storage device for storing one or more programs,

[0057] When the one or more programs are executed by the one or more processors, the one or more processors implement the mirror lattice support structure design method based on topological optimization reconstruction and point cloud reconstruction in the first aspect.

[0058] The application further provides a readable storage medium having a computer program stored thereon, and the program is executed by a processor to implement the mirror lattice support structure design method based on topological optimization reconstruction and point cloud reconstruction in the first aspect.

[0059] The readable storage medium includes but is not limited to: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk and various program code storage media.

[0060] The application further provides a computer program product, and the computer program product includes: a computer program (also referred to as code or instruction), when the computer program is executed, the mirror lattice support structure design method based on topological optimization reconstruction and point cloud reconstruction in the first aspect is executed.

[0061] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, microwave, etc.) mode.

[0062] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Skilled professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0063] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the devices, apparatuses and modules described above can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0064] The above describes the present application in detail in combination with specific embodiments and exemplary examples, but these descriptions cannot be understood as limitations of the present application. Those skilled in the art understand that the technical solutions and their embodiments of the present application can be variously replaced, modified or improved without departing from the spirit and scope of the present application, which all fall within the scope of the present application. The scope of protection of the present application is subject to the appended claims.

[0065] The contents not described in detail in the specification of the present application are the known technology of those skilled in the art.

Claims

1. A mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction, characterized in that, The application relates to a mirror point array support structure design method. The mirror point array support structure topology optimization model is established according to the initial design space model of the mirror point array support structure under the condition of mirror assembly load, and an STL model of the optimal topology layout is outputted; The STL point cloud is subjected to automatic surface reconstruction to obtain a first closed free surface; the STL point cloud is subjected to inward offsetting, and after local modification, the STL point cloud is subjected to automatic surface reconstruction again to generate a second closed free surface; the two closed free surfaces are subjected to geometric processing to generate a solid shell model of the support structure; The inner cavity surface of the solid shell model is subjected to mesh division and STL model generation again, the point array type and cell parameters are specified for point array filling, and the point array is simplified into a beam element finite element model; The beam element end free nodes on the envelope contour boundary of the beam element finite element model are extracted to generate a point cloud, and the point cloud is subjected to triangular mesh reconstruction; The reconstructed triangular mesh is taken as the inner boundary of the solid shell model, and the triangular mesh is assembled with the solid shell model to generate a complete mirror point array support structure finite element simulation model; The mirror point array support finite element model is subjected to simulation verification and iterative optimization under the adjustment state, and if the simulation result does not satisfy a threshold value, the point array density or the shell structure thickness is adjusted in a parameterized mode to realize closed-loop optimization.

2. The mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of claim 1, wherein, The mirror point array support structure topology optimization model is established by taking mirror rigid body displacement and mirror surface figure error minimization as targets and taking volume fraction as a constraint.

3. The mirror point array support structure design method based on topology optimization reconfiguration and point cloud reconstruction of claim 1, wherein, After the step of outputting the STL model of the optimal topology layout, the method further comprises the following steps: evaluating the surface quality of the STL model; if the surface smoothness of the STL model does not satisfy the requirement, the surface smoothness of the STL model is made to satisfy the requirement through mesh redivision and smoothing processing.

4. The mirror point array support structure design method based on topology optimization reconfiguration and point cloud reconstruction of claim 1, wherein, Before the step of automatically reconstructing the STL point cloud to obtain the first closed free surface, the method further comprises the following step: the STL point cloud is subjected to adaptive filtering by setting filtering parameters of minimum point spacing and maximum point spacing.

5. The mirror point array support structure design method based on topology optimization reconfiguration and point cloud reconstruction of claim 1, wherein, The step of automatically reconstructing the STL point cloud to obtain the first closed free surface is implemented by the following mode: the STL point cloud is subjected to automatic surface reconstruction by adopting a NURBS surface fitting algorithm to obtain the first closed free surface.

6. The mirror point array support structure design method based on topology optimization reconfiguration and point cloud reconstruction of claim 1, wherein, The step of extracting the beam element end free nodes on the envelope contour boundary of the beam element finite element model to generate a point cloud and performing triangular mesh reconstruction on the point cloud is implemented by the following mode: the point cloud is projected onto a two-dimensional coordinate plane through a normal line; the projected point cloud is triangulated in the plane to obtain the topological connection relationship of each point, and a spatial region growth algorithm based on Delaunay triangulation is applied in the plane triangulation process; the topological connection between the original three-dimensional points is determined according to the topological connection relationship of the projected points in the plane, and a triangular mesh model is reconstructed.

7. The mirror point array support structure design method based on topology optimization reconfiguration and point cloud reconstruction of claim 1, wherein, After the step of performing simulation verification and iterative optimization on the mirror point array support finite element model under the adjustment state, the method further comprises the following step: the mirror point array support structure finite element simulation model is subjected to statics, dynamics and thermal-mechanical coupling simulation to verify the mirror surface figure accuracy and the structural reliability of the support structure.

8. A mirror point array support structure design apparatus based on topology optimization reconstruction and point cloud reconstruction, characterized by, The application relates to a mirror point array support structure design method. one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, cause the one or more processors to implement the mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of any one of claims 1 to 7.

9. A readable storage medium, characterized by, a computer program product, having stored thereon a computer program, which, when executed by a processor, implements the mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of any one of claims 1 to 7.

10. A computer program product, characterised in that, the computer program product comprises a computer program which, when executed, performs the mirror point array support structure design method based on topology optimization reconstruction and point cloud reconstruction of any one of claims 1 to 7.

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