基于机器视觉的混凝土3D打印几何特征自动提取方法研究

Research on Automatic Extraction Method of Geometric Features of Concrete 3D Printing Based on Machine Vision

近年来,随着混凝土3D打印技术的不断发展,打印成品的质量受到越来越多的关注。打印成品的几何特征已成为评估打印质量的重要指标。针对当前3D打印混凝土几何特征提取中存在的诸如流程复杂、精度有限及缺乏评价指标等问题,本文设计了基于机器视觉的混凝土3D打印几何特征自动提取方法。首先,采用摄像头阵列部署方法获取打印成品的原始图像,并对原图像正畸以提高图像质量;其次,通过语义分割模型U-Net提取打印成品的几何特征,并对得到的结果进行优化;最后,通过量化的指标值,对其进行了可视化并评价打印结果。实验证明,本文提出的几何特征自动提取方法具有速度快、精度高等显著优势;此外,系统化的打印评价指标可为混凝土3D打印质量评估提供借鉴参考。

In recent years,thanks to the continuous development of concrete 3D printing technology,the quality of printed products has attracted more and more attention.The geometric characteristics of printed products have become an important index to evaluate the printing quality.Aiming at solving a series of problems existing in the current 3D printing concrete geometric feature extraction methods e.g.complex process,limited precision and lack of evaluation indicators,this paper designs an automatic extraction method of 3D printing concrete geometric features based on machine vision.Firstly,the camera array deployment method is used to obtain the original image which is orthodontic to improve the image quality.Then,the geometric features of printed products are extracted by semantic segmentation model U-Net,after which the results are optimized.Finally,through the quantitative index value,it is visualized and the print result is evaluated.Experiments have shown that the geometric feature automatic extraction method proposed in this paper has significant advantages such as fast speed and high accuracy.In addition,systematic evaluation indicators can provide reference for the quality evaluation of concrete 3D printing.