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一种基于VPP 3D打印机提高制造精度的虚拟可视化方法。

A virtual visualization method for improving the manufacturing accuracy based VPP 3D printers.

作者信息

Yu Zhengdong, Miao Zhenyu, Liu Zuoyu, Yang Bohan, Zuo Tongxing, Li Xiangqin, Wang Huan, Liu Zhenyu

机构信息

Changchun Institute of Optics Fine Mechanics and Physics (CIOMP), Chinese Academy of Sciences, Changchun, 130033, China.

School of Optoelectronics, University of Chinese Academy of Sciences, Beijing, 100049, China.

出版信息

Heliyon. 2024 Aug 29;10(17):e37051. doi: 10.1016/j.heliyon.2024.e37051. eCollection 2024 Sep 15.

DOI:10.1016/j.heliyon.2024.e37051
PMID:39286113
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11402730/
Abstract

Compared to traditional vat photopolymerization 3D printing methods, pixel blending technique provides greater freedom in terms of user-defined lighting sources. Based on this technology, scientists have conducted research on 3D printing manufacturing for elastic materials, biologically inert materials, and materials with high transparency, making significant contributions to the fields of portable healthcare and specialty material processing. However, there has been a lack of a universal and simple algorithm to facilitate low-cost printing experiments for researchers not in the 3D printing industry. Here, we propose a mathematical approach based on morphology to simulate the light dose distribution and virtual visualization of parts produced using grayscale mask vat photopolymerization 3D printing technology. Based on this simulation, we develop an auto-correction method inspired by circle packing to modify the grayscale values of projection images, thereby improving the dimensional accuracy of printed devices. This method can significantly improve printing accuracy with just a single parameter adjustment. We conducted experimental validation of this method on a vat photopolymerization printer using common commercial resins, demonstrating its feasibility for printing high precision structures. The parameters utilized in this method are comparatively simpler to acquire compared to conventional techniques for obtaining optical parameters. For researchers in non-vat photopolymerization 3D printing industry, it is relatively user-friendly.

摘要

与传统的光固化3D打印方法相比，像素混合技术在用户定义光源方面提供了更大的自由度。基于这项技术，科学家们对弹性材料、生物惰性材料和高透明度材料的3D打印制造进行了研究，为便携式医疗保健和特殊材料加工领域做出了重大贡献。然而，对于非3D打印行业的研究人员来说，一直缺乏一种通用且简单的算法来促进低成本的打印实验。在此，我们提出一种基于形态学的数学方法，以模拟使用灰度掩膜光固化3D打印技术生产的零件的光剂量分布和虚拟可视化。基于此模拟，我们开发了一种受圆形填充启发的自动校正方法，以修改投影图像的灰度值，从而提高打印设备的尺寸精度。该方法只需进行一次参数调整就能显著提高打印精度。我们在一台光固化打印机上使用常见的商业树脂对该方法进行了实验验证，证明了其用于打印高精度结构的可行性。与获取光学参数的传统技术相比，该方法所使用的参数相对更容易获取。对于非光固化3D打印行业的研究人员来说，它相对比较用户友好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/39686ce40488/gr15.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/c4b1062ef8fb/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/328a00c09f01/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/81543d726419/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/b8d15adeb4e0/gr12.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/c832174c8d80/gr14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/39686ce40488/gr15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/3e82e8d1898f/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/e5431d94aca2/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/910ef526c07b/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/9b4f847a824a/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/a19a01e8f7a8/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/6f02c158b51c/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/31722eb5e285/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/04c957fe34dd/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/c4b1062ef8fb/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/328a00c09f01/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/81543d726419/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/b8d15adeb4e0/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/f0158b1f93ff/gr13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/c832174c8d80/gr14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c1b/11402730/39686ce40488/gr15.jpg

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