WO2023231013A1 - Procédé et appareil de reconstruction de domaine de fluide pour fabrication additive, et support de stockage - Google Patents

Procédé et appareil de reconstruction de domaine de fluide pour fabrication additive, et support de stockage Download PDF

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Publication number
WO2023231013A1
WO2023231013A1 PCT/CN2022/096955 CN2022096955W WO2023231013A1 WO 2023231013 A1 WO2023231013 A1 WO 2023231013A1 CN 2022096955 W CN2022096955 W CN 2022096955W WO 2023231013 A1 WO2023231013 A1 WO 2023231013A1
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cross
fluid domain
section
voxel
unsupported
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PCT/CN2022/096955
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English (en)
Chinese (zh)
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张卿卿
贾琇
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西门子股份公司
西门子（中国）有限公司
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Priority to PCT/CN2022/096955 priority Critical patent/WO2023231013A1/fr
Publication of WO2023231013A1 publication Critical patent/WO2023231013A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation

Definitions

  • the present invention relates to the technical field of additive manufacturing, and in particular to an additive manufacturing fluid domain reconstruction method, device and computer-readable storage medium.
  • AM additive manufacturing
  • SLM selective laser melting
  • LPBF laser powder bed fusion
  • embodiments of the present invention provide, on the one hand, an additive manufacturing fluid domain reconstruction method, and on the other hand, an additive manufacturing fluid domain reconstruction device and a computer-readable storage medium, which can realize additive manufacturing. Automatic reconstruction of fabricated fluid domains.
  • a fluid domain reconstruction method for additive manufacturing including: extracting the fluid domain in the current CAD model, and skeletonizing the fluid domain to obtain a skeletonized fluid domain; based on the skeletonized fluid domain, determine Candidate areas for support need to be generated, and target areas within the candidate area from which support cannot be removed are determined; key cross-sectional profiles in the target area are replaced with unsupported cross-sectional profiles based on the principle of minimal area difference; all cross-sectional profiles are used.
  • the cross-section profile is reconstructed into three-dimensional solids and surfaces to obtain a new fluid domain.
  • An additive manufacturing fluid domain reconstruction device including: a first unit, used to extract the fluid domain in the current CAD model and skeletonize the fluid domain to obtain a skeletonized fluid domain; a second unit, Used to determine candidate areas where support needs to be generated based on the skeletonized fluid domain, and determine the target area within the candidate area where support cannot be removed; the third unit is used to determine the key cross-sectional contours in the target area according to The principle of minimum area difference is used to replace unsupported cross-sectional profiles; the fourth unit is used to reconstruct three-dimensional solids and surfaces using all cross-sectional profiles to obtain a new fluid domain.
  • An additive manufacturing fluid domain reconstruction device includes at least one memory and at least one processor, wherein: the at least one memory is used to store a computer program; the at least one processor is used to call the at least one memory stored in A computer program that executes the additive manufacturing fluid domain reconstruction method as described in any of the above embodiments.
  • a computer-readable storage medium has a computer program stored thereon; the computer program can be executed by a processor and implement the fluid domain reconstruction method of additive manufacturing as described in any of the above embodiments.
  • the parameterized unsupported cross-section is reconstructed according to the principle of minimizing the area difference for the support-inaccessible area in the fluid domain. Since the parameterized unsupported cross-section only The corresponding unsupported cross-section can be obtained by changing the corresponding parameters. Therefore, manual reconstruction is not required, and the automatic reconstruction of the fluid domain for additive manufacturing is realized.
  • Figure 1 is an exemplary flow chart of an additive manufacturing fluid domain reconstruction method in an embodiment of the present invention.
  • Figure 2A is a schematic diagram of a CAD model in an example of the present invention.
  • FIG. 2B is a schematic diagram of extracting fluid domains from a CAD model in an example of the present invention.
  • Figure 2C is a schematic diagram of the extraction fluid domain proposed in Figure 2B.
  • Figure 2D is a schematic diagram of all voxel center points in an example of the present invention.
  • Figure 2E is a schematic diagram of a skeleton curve in an example of the present invention.
  • Figure 2F is a schematic diagram of an isoparametric curve in an example of the present invention.
  • Figure 2G is a schematic diagram of key cross-sectional profiles in one example of the present invention.
  • Figure 3 is an exemplary flow chart of a refinement algorithm in an example of the present invention.
  • FIG. 4A is a schematic diagram of the minimum overhang angle ⁇ in an example of the present invention.
  • Figure 4B is a schematic diagram of an inaccessible support removal area in one example of the present invention.
  • FIG. 4B is a schematic diagram of a target area identified for unsupported cross-sectional reconstruction in an example of the present invention.
  • Figure 4D is a schematic diagram of a curve segment allowing unsupported cross-sectional reconstruction in one example of the present invention.
  • Figure 5 is a flowchart of the method for creating an unsupported cross section in an example application.
  • FIG. 6A is a schematic diagram of setting sampling points according to set intervals in an example of the present invention.
  • Figure 6B is a schematic diagram of a tangent vector in an example of the present invention.
  • Figure 7A is a schematic diagram of a sampling point where an unsupported cross section needs to be reconstructed in an example of the present invention.
  • FIG. 7B is a schematic diagram of reconstructing a cross section along a guide curve in an example of the present invention.
  • Figure 7C is a schematic diagram for determining critical cross-sectional areas in an example of the present invention.
  • FIG. 7D is a schematic diagram of adding a cross-sectional curve to a curve network with alignment directions and consistent alignment points in an example of the present invention.
  • Figure 7E is a schematic diagram of the reconstructed fluid domain in an example of the present invention.
  • 8A to 8D are schematic diagrams of parameterized unsupported cross-sections in embodiments of the present invention.
  • Figure 9 is a schematic diagram of the twist angle in the embodiment of the present invention.
  • Figure 10 is an exemplary structural diagram of an additively manufactured fluid domain reconstruction device in an embodiment of the present invention.
  • Figure 11 is an exemplary structural diagram of another additively manufactured fluid domain reconstruction device in an embodiment of the present invention.
  • Figure 1 is an exemplary flow chart of an additive manufacturing fluid domain reconstruction method in an embodiment of the present invention.
  • relevant drawings are correspondingly presented on the right side of Figure 1 .
  • the method may include the following steps:
  • Step S101 Receive the CAD model.
  • the CAD model has been positioned in the optimal direction based on the construction direction Bb.
  • Step S102 Extract the fluid domain from the CAD model, and skeletonize the fluid domain cavity to obtain a skeletonized fluid domain.
  • the skeletonized fluid domain may include: skeleton curves, isoparametric curves and key cross-sectional profiles.
  • standard CAD operations can be first used, such as Boolean operations or surface extraction and stitching as shown in Figure 2B and Figure 2C, to generate a fluid domain (FD, Flow Domain) from the received current CAD model.
  • FD Fluid Domain
  • skeleton curve and related projection curve of the fluid domain are extracted. Specifics may include:
  • the fluid domain can be converted into a surface model composed of triangular surfaces, and then converted into an implicit model defined by a signed distance field through signed distance transformation.
  • the signed distance field is a scalar function dist(x, y, z), which defines the nearest distance from any point (x, y, z) to the object boundary, where positive values indicate that the point is outside the object and negative values indicate The point is inside the object, zero means the point is on the object boundary.
  • Binary voxel models represent objects by exhaustively enumerating voxel occupancies on a spatial grid. For each voxel, a binary value is stored, with 1 indicating True, indicating the presence of material (within the object), and 0 indicating False, indicating the absence of material (outside the object). Specifically, when performing a voxelization operation, the value of each voxel element is determined by the value of the corresponding element in the signed distance array, where negative and zero signed distance values yield a 1 (true) voxel value and positive signed distance values Produces 0 (false) voxel values.
  • the skeleton curve is usually the central axis of the fluid domain, which is a low-dimensional representation of the original object and is the main topological feature.
  • Figure 3 shows an exemplary flowchart of a refinement algorithm in one example of the present invention.
  • the flow chart includes: after receiving the binary voxel model in step 301, performing voxel analysis of the set neighborhood for each voxel in step 302.
  • an octree data structure can be used.
  • the voxels to be deleted can be added to a candidate voxel list; then in step 303 Delete (or retain) the corresponding candidate voxels.
  • the voxels in the candidate voxel list can be deleted.
  • step 304 it is judged whether the remaining voxel models have not changed. If so, step 305 is performed. Based on the remaining voxels, The voxel model obtains a voxel chain with a width of one voxel; otherwise, return to step 302. It can be seen that the thinning algorithm shown in Figure 3 iteratively scans the entire binary voxel model and removes voxels at each iteration until the remaining voxel models stop changing. During each iteration, a list of candidate voxels to be deleted is assembled, then checked sequentially, and the corresponding candidate voxels are deleted (or retained).
  • the resulting skeleton is represented by a network of voxel chains one voxel wide.
  • the center point of each voxel in the skeleton chain can be extracted as shown in Figure 2D, and then curve fitting can be performed on each center point to obtain the skeleton curve as shown in Figure 2E.
  • This skeleton curve can be used as a guide for fluid domain reconstruction. curve.
  • the isoparametric envelope curve is extracted using the fluid domain surface projection method to obtain the isoparametric curve.
  • some key cross-sectional profiles and areas are also obtained based on the geometry of the fluid domain for new geometric evaluation in the next steps. These critical cross-section profiles are perpendicular to the tangent direction of the internal skeleton curves.
  • all the information required for the original fluid domain geometry is collected, namely skeleton curves as guide curves, isoparametric curves and key cross-section profiles.
  • Step S103 Determine candidate areas for which support needs to be generated, and determine target areas within the candidate areas from which support cannot be removed.
  • the support structure generation or overhang check provided by the CAD module or AM build preparation software to apply it to the fluid domain, find the overhang surface, and generate the support structure.
  • the overhang is determined by the angle between the downward surface and the base plate, the overhang angle, as shown in Figure 4A.
  • the minimum overhang angle ⁇ is the smallest manufacturable overhang, ranging from 0° to 90°, with a typical value of 45°.
  • AM when generating supports, an important thing to consider is to evaluate the feasibility of removing the support structure during post-processing, especially supports generated within channels. Based on the resulting support structure or overhang area, a tool accessibility assessment can be used to estimate the feasibility of support removal.
  • region 41 is the inaccessible support removal region and region 42 is the identified fluid domain for unsupported cross-sectional reconstruction.
  • the user can also select the line segments that require unsupported cross-section reconstruction on the previously extracted guide curve and mark the selected line segments to apply for potential unsupported flow channel reconstruction.
  • Cross-sectional shape Users can also preset flow channel cross-sectional shapes based on functional requirements and established design guidelines.
  • the curve segment 43 corresponding to the dotted line is a curve segment that needs to be adapted to the unsupported cross-section
  • the curve segment corresponding to the solid line is a curve segment that does not need to be adapted to the shape of the unsupported cross-section.
  • their cross-sectional shape can be preset to be circular. Store segmentation information for later generation of cross sections.
  • Step S104 Perform parameterized unsupported cross-sectional contour reconstruction in the target area according to the principle of minimizing the difference between the reconstructed cross-sectional area and the original cross-sectional area.
  • FIG. 5 shows a flowchart of a method for creating an unsupported cross section in an example. As shown in Figure 5, the method may include:
  • Step 51 Obtain the guidance curve and information about the preset cross-sectional shape set for line segments other than the line segments corresponding to the target area.
  • the preset cross-sectional shape is mainly aimed at the area where unsupported cross-sectional contour reconstruction is not required, that is, the area outside the target area, such as the area corresponding to the solid line part in Figure 4D, that is, except the area labeled 43 Area outside the indicated area, the preset cross-sectional shape here can be consistent with the shape of the original critical cross-sectional profile of the fluid domain, for example, if its original critical cross-sectional profile is circular, the preset cross-sectional shape in this step The cross-sectional shape may also be circular.
  • Step 52 Generate a series of sampling points with set intervals, such as user-specified intervals, along the guidance curve.
  • the intervals can be uniform or non-uniform, as shown in Figure 6A. After that, starting from the first sampling point in the sampling point sequence, the first sampling point is regarded as the current sampling point.
  • Step 53 Determine whether the position of the current sampling point is located within a curve segment with a preset cross-sectional shape, such as the solid line segment in Figure 4D. If so, proceed to step 54; otherwise, proceed to step 55.
  • sampling points other than the gray sampling points in FIG. 7A are located within the curve segment with the preset cross-sectional shape.
  • Step 54 Create a cross section directly using the preset cross section shape at the location of the sampling point.
  • step 54 may specifically include step 541 and step 542.
  • Step 541 Calculate the first shape parameter according to the geometric relationship between the target cross-sectional area and the preset cross-sectional shape.
  • the target cross-sectional area is determined based on the area of the original critical cross-sectional profile of the fluid domain. For example, as shown in Figure 7C, 1 to 8 show eight key cross-sections.
  • the target cross-sectional area of the sampling point is the area of the critical cross-section; when the sampling point is located outside a certain critical cross-section, then the sampling point
  • the target cross-sectional area of a point can be obtained by fitting at least two adjacent critical cross-sections to obtain the cross-sectional area of the sampling point.
  • Step 542 Create a cross-section of a preset shape based on the first shape parameter at the position of the sampling point. Then proceed to step 57.
  • the radius parameter that is, the first shape parameter
  • the radius parameter will be calculated directly based on the given target cross-sectional area at the current position.
  • a circular cross-section will be created within the range centered on the current sampling point, as shown in Figure 7B as a solid circular cross-section.
  • Step 55 Calculate the tangent vector of the skeleton curve at the sampling point, as shown by the vector indicated by the arrow in Figure 6B; and calculate the cosine value of the current angle ⁇ between the tangent vector and the construction direction Bd.
  • Step 56 Determine whether the value of cos( ⁇ ) is less than or equal to the value of cos( ⁇ ), where ⁇ is the minimum overhang angle. If so, perform step 54; otherwise, perform step 57.
  • Step 57 Create a parameterized unsupported cross-section of a rhombus shape or its derivative shape at the location of the sampling point.
  • the parameterized unsupported cross-section is inscribed in a circle, and the four corners of the corresponding rhombus are all rounded corners.
  • a suitable unsupported cross-section may take the form of a rhombus or a derivative of the rhombus shape as shown in any one of Figures 8A to 8D.
  • Each figure in Figures 8A to 8D is inscribed in a circle with a radius R c .
  • Figure 8A is a general rhombus.
  • the four corners of the corresponding rhombus are all rounded corners.
  • the corresponding radii are: left and right corner radius.
  • R fhl and R fhr top and bottom fillet radii R fvt and R fvb .
  • the rhombus shape can be defined by 6 geometric parameters, namely, the center radius R c , the tilt angle ⁇ , the left and right fillet radii R fhl and R fhr , the top and bottom fillet radii R fvt and R fvb , and the constraints of the shape parameters are and Other specific shapes are derived from the general rhombus shape shown in Figure 8A.
  • the user in order to define the rhombus shape individually, the user can predefine the geometric relationship between the remaining five parameters and solve it based on the target cross-sectional area. For example, you can enter and value, R c can then be solved based on the given shape area and the cross-sectional shape is fully defined. As shown in Figures 7A and 7B, dashed cross-sections are created using diamond shapes at gray sampling points where unsupported shape adaptation is required.
  • step 56 may specifically include the following steps 561 to 563.
  • Step 571 Calculate the rhombus side inclination angle ⁇ of an unsupported cross-section based on the current included angle ⁇ and the minimum overhang angle ⁇ .
  • the inclination angle ⁇ can be calculated from the current included angle ⁇ and the minimum overhang angle ⁇ according to the following formula (1):
  • Step 572 Calculate the second shape parameter according to the inclination angle ⁇ , the target cross-sectional area and the preset geometric relationship.
  • the corresponding R c can be calculated, and the obtained second shape parameters can include: R c , R fv , R fh and beta.
  • the value of S diamond can be determined based on the area of the key cross-section shown in Figure 7C.
  • the corresponding R c can be calculated, and the obtained second shape parameters can include: R c , R f and ⁇ .
  • the value of S droplet can be determined based on the area of the key cross-section shown in Figure 7C.
  • the corresponding R c can be calculated, and the obtained second shape parameter can include: R c , R f and ⁇ .
  • the value of S diamond can be determined based on the area of the key cross-section shown in Figure 7C.
  • Step 573 Create a cross-section of the corresponding shape at the position of the sampling point according to the second shape parameter.
  • Step 58 Determine whether there is a next sampling point. If so, use the next sampling point as the current sampling point and return to step 53; otherwise, execute step 59.
  • Step 59 Export the section created on the skeleton curve.
  • the cross-section will be directly created at the position of the sampling point using the preset cross-sectional shape. If the position of the current sampling point is outside the curve segment with the preset cross-sectional shape, the tangent vector of the guide curve is calculated at the sampling point. The tangent vector and the construction direction vector are known, and the angle between the two can be calculated directly. The cosine of ⁇ . If the value of cos( ⁇ ) is not less than or equal to the value of cos( ⁇ ), where ⁇ is the minimum overhang angle, the cross-sectional shape of the current sampling point will be adjusted to an unsupported shape. Otherwise, the section shape will remain as the default shape.
  • Step S106 Use all cross-sectional contours to reconstruct three-dimensional solids and curved surfaces to obtain a new fluid domain.
  • all cross-sectional profiles and corresponding skeleton curves can be used for reconstruction at the same time.
  • the three-dimensional solid or surface can be reconstructed using the lofting operation available in the CAD software to form a new fluid domain.
  • Lofting is a traditional CAD technique for creating curved and smooth shapes by first specifying a network of curves that approximate the desired shape, and then interpolating these curves using smooth surfaces.
  • Figure 7D cross-section curves are added to a curve network with aligned directions and consistent alignment points.
  • Figure 7E shows the final lofted surface of the reconstructed fluid domain.
  • the twist angle ⁇ between different reconstructed cross-sectional profiles in the two target areas should be within a set angle range, such as As shown in Figure 9, for the original circular cross-sectional profile 91, the first point 92 and the second point 93 respectively correspond to the projection of the same isoparametric curve of different reconstructed cross-sectional profiles, then the angle between the two points and the center is ⁇ should be within a set angle range.
  • step S106 the following step S105 may be further included: determining whether the twist angle ⁇ between different reconstructed cross-sectional profiles is within a set angle range such as the control angle ⁇ c .
  • twist angle ⁇ exceeds the control angle ⁇ c , then the relevant parameters determined in the above steps need to be adjusted and optimized, such as ⁇ , ⁇ and cross-section fillet radius, etc. to optimize the unsupported cross-section in line with the construction direction and the original geometry skeleton, and then based on the adjustment
  • the corresponding twist angle ⁇ is calculated again for the subsequent parameters until the twist angle ⁇ is within the range of the control angle ⁇ c .
  • users can define the control angle ⁇ c and the optimal iteration termination threshold to adapt to various application scenarios. This step will ensure that the final reconstructed geometry does not suffer from severe surface deformations and maintains the original design intent and performance as closely as possible.
  • the obtained reconstructed fluid domain will become the core component of subsequent CAD operations to generate unsupported manufacturable geometry for inaccessible areas.
  • the reconstructed geometry may also be subjected to simulation verification of reconstructed fluid domain, such as fluid and heat, that is, step S107.
  • the fluid domain reconstruction method for additive manufacturing in the embodiment of the present invention has been described in detail above, and the fluid domain reconstruction device for additive manufacturing in the embodiment of the present invention will be described in detail below.
  • the additive manufacturing fluid domain reconstruction device in the embodiment of the present invention can be used to implement the additive manufacturing fluid domain reconstruction method in the embodiment of the present invention.
  • the present invention for details not disclosed in detail in the device embodiment of the present invention, please refer to the present invention. Corresponding descriptions in method embodiments.
  • Figure 10 is an exemplary structural diagram of an additively manufactured fluid domain reconstruction device in an embodiment of the present invention. As shown in Figure 9, the device may include: a first module 1001, a second module 1002, a third module 1003 and a fourth module 1004.
  • the first unit 1001 is used to receive the current CAD model, extract the fluid domain in the current CAD model, and skeletonize the fluid domain to obtain a skeletonized fluid domain.
  • the second unit 1002 is configured to determine candidate areas where support needs to be generated based on the skeletonized fluid domain, and determine target areas within the candidate areas where support cannot be removed.
  • the third unit 1003 is used to perform unsupported cross-sectional profile replacement in the target area according to the principle of minimizing the difference between the reconstructed cross-sectional area and the original cross-sectional area.
  • the fourth unit 1004 is used to reconstruct three-dimensional solids and surfaces using all cross-sectional contours to obtain a new fluid domain.
  • the additively manufactured fluid domain reconstruction device provided by this embodiment of the invention may be embodied in various ways.
  • the additively manufactured fluid domain reconstruction device can be compiled into a plug-in installed in a smart terminal by using an application programming interface that conforms to specific rules, or can be packaged into an application for users to download and use.
  • the additive manufacturing fluid domain reconstruction device can be implemented in a variety of plug-in forms, such as ocx, dll and cab.
  • the additively manufactured fluid domain reconstruction device provided by this implementation of the present invention can also be implemented by using specific technologies, such as Flash plug-in technology, RealPlayer plug-in technology, MMS plug-in technology, MIDI personnel plug-in technology or ActiveX plug-in technology.
  • the fluid domain reconstruction method for additive manufacturing can be stored in various storage media in an instruction storage manner or an instruction set storage manner.
  • These storage media include but are not limited to: floppy disk, optical disk, DVD, hard disk, flash memory, USB flash memory, CF card, SD card, MMC card, SM card, memory stick and xD card.
  • the additive manufacturing fluid domain reconstruction method provided by this embodiment of the present invention can also be applied to flash memory (Nand-flash)-based storage media, such as USB flash drives, CF cards, SD cards, SDHC cards, MMC card, SM card, memory stick and xD card.
  • flash memory Nand-flash-based storage media
  • USB flash drives such as USB flash drives, CF cards, SD cards, SDHC cards, MMC card, SM card, memory stick and xD card.
  • the operating system operating in the computer can not only implement the program code read by the computer from the storage medium, but also implement part or all of the actual operations by using instructions based on the program code to implement the above embodiments. function of any embodiment.
  • FIG. 11 is an exemplary structural diagram of another additively manufactured fluid domain reconstruction device in an embodiment of the present invention.
  • the device can be used to perform the method shown in Figure 1, or to implement the device in Figure 10.
  • the device may include at least one memory 1101 and at least one processor 1102.
  • some other components can be included, such as communication ports, input/output controllers, network communication interfaces, etc. These components communicate via bus 1103 and so on.
  • At least one memory 1101 is used to store computer programs.
  • the computer program can be understood as including various modules of the device shown in FIG. 10 .
  • at least one memory 1101 may store an operating system and the like.
  • Operating systems include but are not limited to: Android operating system, Symbian operating system, windows operating system, Linux operating system, etc.
  • At least one processor 1102 is configured to call a computer program stored in at least one memory 1101 to execute the additive manufacturing fluid domain reconstruction method described in the example of the present invention.
  • the processor 1102 can be a CPU, a processing unit/module, an ASIC, a logic module or a programmable gate array, etc., and it can receive and send data through a communication port.
  • the input/output controller has a display and an input device for inputting, outputting and displaying relevant data as a human-computer interaction module.
  • the parameterized unsupported cross-section is reconstructed according to the principle of minimizing the area difference for the support-inaccessible area in the fluid domain. Since the parameterized unsupported cross-section only The corresponding unsupported cross-section can be obtained by changing the corresponding parameters. Therefore, manual reconstruction is not required, and the automatic reconstruction of the fluid domain for additive manufacturing is realized.
  • the present invention proposes an efficient and automatic flow chamber area design and reconstruction scheme to avoid the generation of inaccessible supports in metal SLM post-processing.
  • the advantages of the present invention can be reflected in the following three aspects:

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Abstract

Des modes de réalisation de la présente invention concernent un procédé et un appareil de reconstruction de domaine de fluide pour la fabrication additive, et un support de stockage. Le procédé consiste à : recevoir un modèle de CAO actuel ; extraire un domaine de fluide dans le modèle de CAO actuel, et squelettiser le domaine de fluide pour obtenir un domaine de fluide squelettisé ; déterminer, sur la base du domaine de fluide squelettisé, une zone candidate où un support doit être généré, et déterminer une zone cible où le support ne peut pas être retiré dans la zone candidate ; effectuer une reconstruction de contour de section transversale non prise en charge dans la zone cible selon un principe de minimisation de la différence entre la zone d'une section transversale reconstruite et la zone d'une section transversale d'origine ; et effectuer une reconstruction de surface tridimensionnelle et de surface incurvée en utilisant tous les contours de section transversale pour obtenir un nouveau domaine de fluide. Selon la solution technique des modes de réalisation de la présente invention, une reconstruction de domaine de fluide peut être mise en œuvre de manière efficace et automatique.
PCT/CN2022/096955 2022-06-02 2022-06-02 Procédé et appareil de reconstruction de domaine de fluide pour fabrication additive, et support de stockage WO2023231013A1 (fr)

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CN110210481A (zh) * 2019-06-06 2019-09-06 福建师范大学 一种基于凹形缝隙区域识别的终板自动分离方法
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