WO2020133310A1 - 基于自适应内部支撑结构的3d打印方法 - Google Patents

基于自适应内部支撑结构的3d打印方法 Download PDF

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WO2020133310A1
WO2020133310A1 PCT/CN2018/125213 CN2018125213W WO2020133310A1 WO 2020133310 A1 WO2020133310 A1 WO 2020133310A1 CN 2018125213 W CN2018125213 W CN 2018125213W WO 2020133310 A1 WO2020133310 A1 WO 2020133310A1
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layer
area
slice
support structure
dimensional model
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PCT/CN2018/125213
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English (en)
French (fr)
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毋立芳
毛羽忻
赵立东
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北京工业大学
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Priority to CN201880100558.3A priority Critical patent/CN113784831B/zh
Priority to PCT/CN2018/125213 priority patent/WO2020133310A1/zh
Priority to US17/419,429 priority patent/US20220072792A1/en
Publication of WO2020133310A1 publication Critical patent/WO2020133310A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/40—Structures for supporting 3D objects during manufacture and intended to be sacrificed after completion thereof
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/30—Auxiliary operations or equipment
    • B29C64/386—Data acquisition or data processing for additive manufacturing
    • 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
    • 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
    • B33Y80/00—Products made by additive manufacturing
    • 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
    • B33Y10/00—Processes of additive manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P10/00—Technologies related to metal processing
    • Y02P10/25—Process efficiency

Definitions

  • the invention is applied to the generation of the internal support structure of the model 3D printing. According to the structural difference of different parts of the model, two different internal support structures that can be applied to different structures are added. In the case of ensuring a certain model strength, printing materials can be saved.
  • 3D printing is a rapid prototyping technology, based on digital model files, using powdery metals or plastics and other adhesive materials to construct objects by layer-by-layer printing.
  • the most prominent advantage of this technology is that it can generate parts of any shape directly from computer graphics data without mechanical processing or any mold, thereby greatly shortening the product development cycle, increasing productivity and reducing production costs.
  • the main purpose of the present invention is to generate a 3D printing support structure from a 2D to 3D biological structure. This method reduces the problem of high material consumption of traditional solid structures, and at the same time increases the strength of the specified direction of the model through an adaptive algorithm, which has good practical significance and theoretical research value for ensuring structural strength and saving printed materials.
  • the present invention builds a mechanical device similar to a biological body or a part of it through research on the structure of a biological body, so that the model structure design is more rooted.
  • the similar functions can be realized by structural similarity, and the strength, toughness and practicality can also be simulated and verified.
  • Combining 3D printing model design with bionic technology can achieve highly optimized and coordinated results, thereby improving the adaptability of the designed model to the environment.
  • the crystal structure such as diamond, belongs to the simple substance of carbon. It is a molecular structure with excellent physical properties such as super-hardness, abrasion resistance, thermal sensitivity, heat transfer, semiconductor and transparent.
  • the Mohs hardness of the diamond is 10. Since it has the highest hardness among natural substances, it is used in the internal support structure material of the model in the present invention.
  • the present invention proposes that the design algorithm of the internal support structure of the three-dimensional model is a description based on the biological structure and is a research conducted from the perspective of the printable layer.
  • Figure 1 is a framework for the design scheme of a skeletal muscle-based support structure
  • Figure 2 is a cross-sectional view of skeletal muscle and basic structural unit cutting
  • Figure 4 is the synthesis of a larger area of skeletal muscle images
  • Figure 5 is an example of fusion of model slice structure and biological structure
  • Figure 6 is a graph of the results of the fixed groove
  • Figure 7 is an example of layered model processing
  • Figure 8 is a partial model slice image
  • Figure 9 is the area ratio change curve
  • Figure 10 is a schematic diagram of key slice processing
  • Figure 11 is a cross-sectional view of the model
  • Figure 12 is the force analysis diagram of the model.
  • the invention is based on 2D slice images for processing.
  • the system includes a computer and FDM technology 3D printer, and an internal support structure can be generated for any given model.
  • reference is first performed as a support structure configuration diagram of a biological extract P (skeletal structure applications herein), the base configuration of an image extraction lines, grid lines P X to give, as an internal support structure model Layer diagram.
  • the skeletal muscle support structure needs to be designed adaptively according to the strength requirements of the model, that is, the support area of each slice is estimated according to the support strength, and the minimum area support that meets the requirements is comprehensively considered. area. Based on this slice, the slice structure of other layers is adaptively determined. Finally, the 3D reconstruction algorithm is used to restore the 3D model and print it.
  • Figure 2(a) is a cross-sectional view of skeletal muscle.
  • muscle fibers are the basic unit of skeletal muscle. Multiple muscle fibers form a fiber bundle.
  • the composition of the fiber bundle is arbitrary, and the joints around the fiber bundle
  • the thickness of the tissue membrane is small, which maintains the uniformity of the skeletal muscle distribution structure.
  • the connective tissue membrane that wraps multiple fiber bundles is relatively thick, destroying the uniformity of the skeletal muscle structure. Therefore, the slice structure should avoid thicker connective tissue membranes, with muscle fibers and fiber bundles as the main structure. Then the basic biological structural unit is obtained by cutting and the subsequent processing work.
  • Biological structure pre-processing includes biological structure image expansion and image segmentation algorithms.
  • the watershed algorithm has a good response to weak edges, which is a guarantee for closed continuous edges.
  • the result of the transformation is the water collection basin image of the input image, and the boundary point between the water collection basins is the watershed. Obviously, the watershed represents the maximum point of the input image.
  • FIG. 2(b) shows the basic structural unit of the cut.
  • the gray scale of the muscle fiber area is small, and the connective tissue area is theoretically a white area. However, due to various factors, these areas are actually gray-white interlaced areas, so The result of a simple binarization method is not very satisfactory.
  • Figure 3(a) is the binarized result image of Figure 2(b). It can be seen that the connective tissue area is not completely segmented, and some areas are cut off, which makes the support area disconnected.
  • FIG. 3(b) is a result diagram after the processing in FIG. 2(b), that is, a watershed method segmentation result image. It can be seen that the watershed method divides the continuous connective tissue area (support area), and the resulting image meets the application requirements. For models with larger sizes or larger strength requirements, the skeletal muscle texture generated in the previous section will appear relatively sparse and may not meet the given strength requirements. In order to ensure that the texture structure has the same stress on all four sides, flip and expand Figure 2(b) and get the final effect picture, as shown in Figure 4.
  • Figure 5(a) is the model "fixed groove”
  • Figure 5(b) is the solid slice 440th layer structure of the fixed groove model
  • Figure 5(c) is the slice of the hollow structure of the model.
  • the model slice and the basic structure image or the expanded image of the basic structure are ANDed to obtain the structure of the layer, as shown in the fusion result image in FIG. 5(d).
  • the purpose of the model analysis is to analyze the pressure and pressure of each slice according to the support strength requirements, further estimate the minimum required support area according to the pressure requirements, calculate the minimum support area and existing area ratio, determine the key slice according to the area ratio, and determine the key slice according to the area ratio.
  • the area ratio of the slice determines the processing method required to change the structure of the critical slice.
  • Figure 7 is a model cat. First, the model is sliced to obtain all slice images, and the existing support area S 0 of each slice is calculated. Fig. 8 is a slice image every 20 layers.
  • the self-weight of the model is 160 grams
  • the total pressure F of each slice can be calculated.
  • the minimum area required for each slice (S min ) the weight of a single layer is equal to the area of the layer times the height and the specific gravity of the material.
  • the pressure from the model's own weight is only on the 0-279 layer.
  • the 280th layer has an external force of 100 Newtons. From this layer, the pressure on each layer suddenly increases, and the minimum area required It also gets bigger.
  • the slice corresponding to the maximum area ratio as the key slice. If the maximum area ratio is greater than 1, it means that the existing area cannot support the strength required by the existing stress, and the existing support area needs to be expanded and expanded by a pixel-by-pixel expansion method. The existing area is expanded by the width of a pixel point, and the area ratio is recalculated. If the area ratio is still greater than 1, the expansion is continued. If the ratio is less than or equal to 1, stop expansion, and determine how many pixels of the expansion area of the support area is expanded.
  • the ratio of the maximum supporting area to the existing area is less than 1, it means that the existing area supports require a surplus of stress, and the existing supporting area needs to be reduced, and the method of item-by-item corrosion is also adopted.
  • the existing area corrodes a pixel dot width, and the area ratio is recalculated. If the ratio is greater than 1, the corrosion is continued. Otherwise, if the ratio is less than or equal to 1, the corrosion is stopped, and the area of the support area is reduced by how many pixel dot widths are corroded.
  • the key slice is the 920th slice, and the area ratio of this slice is 1.47, indicating that the existing support area is insufficient, so the support area in the existing slice structure needs to be expanded.
  • the width of the expanded pixel is finally determined to be 6 pixels.
  • FIG. 10(a) is the slice image of the 920th layer
  • FIG. 10(b) is the result of the expansion of 6 pixels image.
  • Fig. 6 is a simulation result diagram, in which Fig. 6(a) is a cross-sectional view of the target model, and 6(b) is a cross-sectional view thereof. You can see the clear internal texture structure.
  • Figures 11 and 12 are verification simulation experiments, where Figures 11(a) and 12(a) are solid structures, Figures 11(b) and 12(b) are hollow structures, and Figures 11(c) and 12 are (c) is the skeletal muscle structure.

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  • Chemical & Material Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Materials Engineering (AREA)
  • Manufacturing & Machinery (AREA)
  • Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Optics & Photonics (AREA)
  • Processing Or Creating Images (AREA)

Abstract

一种基于自适应内部支撑结构的3D打印方法，包括下述步骤：S1：将支撑结构的基准生物结构图进行图像提取，得到多层网格纹路，作为三维模型内部支撑结构的多个层图；S2：将三维模型逐层分离出多层结构，每一层进行二值化与掏空处理得到多张图片；S3：将步骤S1中得到的每个层图与步骤S2中得到的相应图片进行融合，得到多个最终的切片层结构；S4：根据三维模型强度需求，确定每个切片层中支撑结构的支撑面积；S5：对三维模型分析进行自适应结构设计，并调整强度材料比；S6：通过三维重建算法还原回三维模型并进行打印。

Description

基于自适应内部支撑结构的3D打印方法 技术领域
本发明应用于模型3D打印内部支撑结构的生成，根据模型不同部位的结构差异，添加两种不同的可以应用于不同结构的内部支撑结构。在保证一定模型强度的情况下，可节省打印材料。
背景技术
3D打印是一种快速成形技术，以数字模型文件为基础，运用粉末状金属或塑料等可粘合材料，通过逐层打印的方式来构造物体的技术。该项技术最突出的优点是无需机械加工或任何模具，就能直接从计算机图形数据中生成任何形状的零件，从而极大地缩短产品的研制周期，提高生产率和降低生产成本。
虽然3D打印技术带来了科技的高速发展，同样这种新兴产业也会有多种包括强度、精度、材料限制、成本等问题。特别是可使用材料非常有限，成本高昂且单一。而传统的模型设计为实心结构，虽具有最高的强度，但是由于总体积限制而带来的打印机行走轨迹增长以及材料成倍消耗。为了避免这种问题，最简单的方式即为挖空内部，留下“外壳”。但此类做法会造成强度的下降甚至于失去模型原有的功能。因此在掏空的基础上再内部添加额外的支撑，在保证必要的强度下尽量减少模型材料的使用量，以达到一个平衡的效果。
又因为一般模型具有复杂性，不同部分的力学结构不尽相同，不能用一种内部支撑结构统一处理，这会造成因脆弱部位的强度需求而增大整体的材料用量，进而增加材料的浪费。
发明内容
本发明主要目的是将生物结构通过2D到3D的方式生成3D打印支撑结构。该方法减少了传统实心结构材料消耗大的问题，同时通过自适应算法增加对模型指定方向的受力强度，对保证结构强度、节约打印材料有较好的实际意义与理论研究价值。
本发明通过生物肌体构造的研究，建造类似生物体或其中一部分的机械装置，使模型结构设计更为有根可循。以结构相似性实现其相 近功能，亦可对其强度、韧度、实用性进行模拟仿真与实体校验。将3D打印模型设计与仿生技术相结合，即可达到高度优化与协调性的结果，进而提高所设计模型对环境的适应能力。
而晶体结构，例如金刚石，属于碳的单质。是一种具有超硬、耐磨、热敏、传热导、半导体及透远等优异的物理性能的分子结构。钻石的摩氏硬度为10。由于在自然界物质中硬度最高，因此在本发明中被用于模型的内部支撑结构材料。
因此本发明提出三维模型内部支撑结构设计算法是一种基于生物结构的描述，是从可打印层角度所进行的研究。
本发明的技术方案由如下几个步骤实现：
1)将作为支撑结构的基准生物结构图进行提取，得到完整的纹理结构图像。
2)对得到的纹理图与需要添加内部支撑结构的模型切片进行融合处理，得到完整并附带内支撑结构的切片图。
3)对模型分析进行自适应结构设计，并调整强度材料比。
4)通过三维重建算法还原立体模型。
5)对模型进行模拟实验以验证算法有效性。
下面结合附图和实施步骤对本发明做详细描述。
附图说明
图1为基于骨骼肌的支撑结构设计方案框架；
图2为骨骼肌截面图和基本结构单元裁切；
图3为两种算法结果；
图4为合成更大面积的骨骼肌图像；
图5为模型切片结构与生物结构融合示例；
图6为固定槽结果图；
图7为模型分层处理示例；
图8为部分模型切片图像；
图9为面积比变化曲线；
图10为关键切片处理示意图；
图11为模型横截面图；
图12为模型受力分析图。
具体实施方式
本发明基于2D切片图像进行处理，系统包括计算机和FDM技术3D打印机，并对任意给定模型都可以生成内部支撑结构。如图1所示，首先将作为支撑结构的基准生物结构图P进行提取(本文应用为骨骼肌结构)，将结构的基础纹路进行图像提取，得到网格纹路P x，作为模型内部支撑结构的层图。再将三维模型一层一层分离出N层结构，每一层被作为一张图片进行二值化与掏空处理，处理得到N i(i＝1,2,3,4...)，再将P x与N i进行合成可得到最终的切片层结构。并进行判断是否完成所有切片的融合。由于模型每层结构并非最优强度材料比，需要根据模型强度需求自适应地设计骨骼肌支撑结构，即为根据支撑强度，估计每一个切片的支撑区域面积，综合考虑得到满足要求的最小面积支撑区域。以该切片为基准，自适应地确定其它层切片结构。最后通过三维重建算法还原回三维模型并进行打印。
具体实施方式如下所述：
(1)图2(a)为骨骼肌的截面图，从图中可以看出，肌纤维是骨骼肌的基本单元，多个肌纤维组成纤维束，纤维束的组成形态任意，纤维束周围的结体组织膜的厚度较小，保持了骨骼肌分布结构的均匀性。包裹多个纤维束的结缔组织膜则比较厚，破坏了骨骼肌结构的均匀性。因此切片结构应避开较厚的结缔组织膜，以肌纤维和纤维束为主要组成结构。然后通过裁剪获得基本生物结构单元并进行后续的处理工作。
生物结构预处理包括生物结构图像拓展和图像分割算法。对于分割方式，分水岭算法对微弱边缘具有良好的响应，是得到封闭连续边缘的保证。其变换所得到的是输入图像的集水盆图像，集水盆之间的边界点即为分水岭。显然，分水岭表示的是输入图像极大值点。
图像分割的主要目的是精确分割出肌纤维(深色)和结缔组织(白色)区域，白色区域对应支撑区域。图2(b)示出了裁切的基本结构单元，其中肌纤维区域灰度较小，结缔组织区域理论上为白色区域，但是由于种种因素的影响，这些区域实际上是灰白交错的区域，因此用 简单的二值化方法结果不很理想。图3(a)为图2(b)二值化后的结果图像，可以看出，结缔组织区域没有完整的分割出来，有些地方被截断，这样就使得支撑区域不连通。
图3(b)为图2(b)处理后的结果图，即分水岭方法分割结果图像。可以看出分水岭方法分割得到了连续的结缔组织区域(支撑区域)，结果图像满足应用需求。对于尺寸较大、或者强度需求较大的模型，上一节生成的骨骼肌纹理结构会显得相对稀疏，可能达不到给定的强度要求。为保证纹理结构在四面都有相同受力情况，对图2(b)进行翻转拓展，并得到最终效果图，如图4所示。
(2)得到支撑结构的纹理图后，即可对目标模型添加内部支撑结构。如图5所示，图5(a)为模型“固定槽”，图5(b)为固定槽模型的实心切片第440层结构，图5(c)为该模型掏空结构的切片，将模型切片与基本结构图像或者基本结构的拓展图像进行“与”运算，即可得到该层的结构，如图5(d)中的融合结果图像所示。
(3)模型分析的目的是根据支撑强度需求，分析每层切片压力和压强，进一步根据压强要求估计最小要求支撑面积，计算最小支撑面积和已有面积比，根据面积比确定关键切片，根据关键切片的面积比，确定改变关键切片结构需要的处理方法。
图7为模型猫，首先对模型进行切片处理，得到所有切片图像，计算每层切片的现有支撑面积S 0。图8为每隔20层的一个切片图像。
进一步计算特定压力F下，每一层切片面积(S 0)、单层重量(G s)、材料比重(d)的关系。模型自重160克，设在模型猫的头顶加压力F＝100牛顿，模型切片厚度H＝0.01mm，材料比重d＝0.3575mg/mm 3，材料能够承受的最大压强P＝300Pa。可计算出每层切片的压力F 总。进一步计算每层切片要求的最小面积(S min)，单层重量等于该层面积乘以高度以及材料比重。由于模型头顶位于第280层，因此，第0-279层只有模型自重带来的压力，第280层开始有100牛顿的外力，从该层开始各层承受的压力突然变大，要求的最小面积也变大。
从图9中可以看出，第920层面积比最大，因此，我们得到第920层为关键层。
首先确定最大面积比对应的切片为关键切片。如果最大面积比大于1，则说明现有面积不能支撑现有应力要求的强度，需要对现有支撑面积进行扩张，采用逐像素膨胀的方法进行扩展。现有面积膨胀一个象素点宽度，重新计算面积比，如果面积比仍然大于1，则继续膨胀。如果比值小于等于1，则停止膨胀，确定支撑区域放大面积为膨胀多少像素点宽度。
如果最大支撑面积和现有面积比小于1，说明现有面积支撑要求应力有盈余，需要对现有支撑面积进行缩减，也采用逐项素点腐蚀的方法。现有面积腐蚀一个象素点宽度，重新计算面积比，如果比值大于1则继续腐蚀，否则如果比值小于等于1，则停止腐蚀，确定支撑区域缩小面积为腐蚀多少象素点宽度。
关键切片为第920层切片，该层切片的面积比为1.47，说明现有支撑面积不足，因此需要对现有切片结构中的支撑区域进行膨胀。通过逐像素膨胀，最终确定膨胀像素宽度为6像素。
其它层的已有支撑面积按照关键层的操作要求膨胀/腐蚀N个像素点宽度，即可得到满足应力要求的每层支撑结构。对于图中第920层切片图像，原始切片图像以及膨胀6像素点的结果图像如图10所示，其中图10(a)为第920层切片图像，图10(b)为膨胀6像素的结果图像。
(4)利用行进立方体方法(MarchingCubes)进行切片的三维结构重建，可得到已添加内部支撑结构的三维模型。图6为仿真结果图，其中图6(a)为目标模型的剖面图，6(b)为其截面图。从中可看到清晰的内部纹理结构。
(5)图11和图12为验证仿真实验，其中，图11(a)、12(a)为实心结构，图11(b)、12(b)为空心结构，图11(c)、12(c)为骨骼肌结构。
从下面表1中可看到本算生成的模型节省了9.884％，而强度几乎保持一致。
表1体积与强度比较
  实心体积 空心体积 骨骼肌体积 体积比 压力值
猫模型 1131.74 111.86 1019.88 9.884％ 120

Claims (6)

  1. 一种基于自适应内部支撑结构的3D打印方法，包括下述步骤：
    S1：将支撑结构的基准生物结构图进行图像提取，得到多层网格纹路，作为三维模型内部支撑结构的多个层图；
    S2：将三维模型逐层分离出多层结构，每一层进行二值化与掏空处理得到多张图片；
    S3：将步骤S1中得到的每个层图与步骤S2中得到的相应图片进行融合，得到多个最终的切片层结构；
    S4：根据三维模型强度需求，确定每个切片层中支撑结构的支撑面积；
    S5：对三维模型分析进行自适应结构设计，并调整强度材料比；
    S6：通过三维重建算法还原回三维模型并进行打印。
  2. 如权利要求1所述的3D打印方法，其中，对于动物模型而言，基于肌纤维之间的结缔组织构建支撑结构。
  3. 如权利要求2所述的3D打印方法，其中，在步骤S1中，通过分水岭方法分割得到的连续的结缔组织区域作为支撑区域。
  4. 如权利要求3所述的3D打印方法，其中，在步骤S1中，对于每个层图，在从中裁切出的区块中确定支撑区域，并将该区块中的支撑区域翻转拓展以确定增大的区块中的支撑区域。
  5. 如权利要求1至4中任一项所述的3D打印方法，其中，在步骤S4中，在每个切片层中的支撑面积大于该切片层面积的情况下，采用逐像素膨胀法扩展该切片层的尺寸。
  6. 如权利要求1至5中任一项所述的3D打印方法，其中，在步骤S4中，在每个切片层中的支撑面积小于该切片层面积的情况下，采用逐像素点腐蚀法缩减支撑面积。
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