Structural Optimization Method of Additive Manufacturing Model Based on Point Cloud Data

被引：0
|
作者：
Xue K. [1 ]
Guo R. [1 ]
Huang H. [1 ]
Huang H. [1 ]
机构：
[1] School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2023年 / 34卷 / 20期
关键词：
additive manufacturing; point cloud data; self-supporting algorithm; structure optimization;
D O I：
10.3969/j.issn.1004-132X.2023.20.011
中图分类号：
学科分类号：
摘要：
Due to the characteristics of layer by layer accumulation in additive manufacturing, it was necessary to consider the correct forming of overhanging structures in the forming processes to avoid the formation of redundant support structures in the structural optimization processes. An optimization method for 3D model structure was proposed herein. Firstly, the point cloud data method was used to process the 3D model to obtain the contour features. Then the model was divided according to different features. Finally, the corresponding internal ellipsoid structures were established according to different external features, and the self-supporting structures were rebuilt in the interior in order to ensure that the optimized structure molding process would not generate extra support because of the special structure. The experimental results show that the method proposed herein may reduce the molding time and material cost by 16.4% and 12% on average respectively on the premise of guaranteeing the performance of the solid model with four different characteristic models as examples. © 2023 China Mechanical Engineering Magazine Office. All rights reserved.
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页码：2482 / 2488
页数：6
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