航空制造技术2024,Vol.67Issue(21) :62-67.DOI:10.16080/j.issn1671-833x.2024.21.062

基于图像分割的激光沉积制造变形测量方法

Laser Deposition Manufacturing Deformation Measurement Method Based on Image Segmentation

刘志伟 杨光 王伟
航空制造技术2024,Vol.67Issue(21) :62-67.DOI:10.16080/j.issn1671-833x.2024.21.062

基于图像分割的激光沉积制造变形测量方法

Laser Deposition Manufacturing Deformation Measurement Method Based on Image Segmentation

刘志伟 1杨光 1王伟2
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作者信息

  • 1. 沈阳航空航天大学机电工程学院,沈阳 110136
  • 2. 沈阳航空航天大学航空制造工艺数字化国防重点学科实验室,沈阳 110136
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摘要

在激光沉积制造加工过程中,热累积和热循环等复杂的热力演化会导致基板与制件产生整体弯曲变形.为了避免过大的变形导致零件尺寸精度降低,对加工过程中产生的变形进行测量尤为重要.本文搭建了双目视觉变形测量系统,采用图像分割技术实现对目标区域的提取,从而过滤掉增材制造背景的干扰.研究图像分割与多种立体匹配算法的结合,并选用Census算法实现分割后图像的视差图求取.最后,采用奇异值分解法拟合基准平面,实现对变形值的获取.试验表明,搭建的测量系统可以实现层间变形量的测量,本文提出的方法在保证测量精度的同时提高了测量效率.

Abstract

In the process of laser deposition manufacturing,the complex thermal evolution such as heat accumulation and thermal cycle will lead to the overall bending deformation of the substrate and the parts.In order to avoid the decrease of dimensional accuracy of parts caused by excessive deformation,it is particularly important to measure the deformation caused by machining.In this thesis,a binocular vision deformation measurement system is built,and the image segmentation technology is used to extract the target area to filter out the interference of the additive manufacturing background.The combination of image segmentation and various stereo matching algorithms is studied,and the Census algorithm is used to obtain the disparity map of the segmented image.Finally,the singular value decomposition method is used to fit the reference plane to obtain the deformation value.Experiments show that the measurement system can realize the measurement of interlayer deformation.The method proposed in this paper improves the measurement efficiency while ensuring the measurement accuracy.

关键词

激光沉积制造(LDM)/弯曲变形/双目视觉/图像分割/Census算法

Key words

Laser deposition manufacturing(LDM)/Bend deformation/Binocular vision/Image segmentation/Census algorithm

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出版年

2024
航空制造技术
北京航空制造工程研究所

航空制造技术

CSTPCD北大核心
影响因子:0.403
ISSN:1671-833X
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