Automated Print Quality Assessment Method for 3D Printing AI Data Construction

被引:0
作者
Yoo, Hyun-Ju [1 ]
Moon, Nammee [1 ]
机构
[1] Hoseo Grad Sch Venture, Dept Convergence Engn, Seoul, South Korea
来源
JOURNAL OF INFORMATION PROCESSING SYSTEMS | 2022年 / 18卷 / 02期
关键词
Data Construction; Dimensional Accuracy; Field-of-View (FOV); Quality Assessment; 3D Printing;
D O I
10.3745/JIPS.04.0240
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.
引用
收藏
页码:223 / 234
页数:12
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