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基于机器视觉的盘类零件尺寸在线测量方法。

Online measurement method for dimensions of disk parts based on machine vision.

机构信息

School of Mechanical Engineering, Changchun Guanghua University, Changchun, China.

School of Mechanical and Aerospace Engineering, Jilin University, Changchun, China.

出版信息

PLoS One. 2024 Jul 25;19(7):e0307525. doi: 10.1371/journal.pone.0307525. eCollection 2024.

DOI:10.1371/journal.pone.0307525
PMID:39052667
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11271902/
Abstract

Online measurement of disk part dimensions by the standard industrial camera features low cost, high efficiency and good universality, but the impact of projection distortion and end face chamfer on measurement is needed to overcome. Present work presents a measurement method to resolve above issues based on machine vision. To improve the measurement accuracy, lower end face of a disk part is determined as calibration plane and the upper end face is measurement plane. To reduce the impact of projection distortion and chamfer on measurement, the measurement points are reconstructed on the measurement plane by re-projection. Then, the inner and outer diameters of disk parts are measured by circle geometric fitting, and the thickness is calculated by the measurement plane position. The experimental results show that the method can online measure disk part dimensions just by a single image, and accuracy meets the requirements of universal grade disk parts.

摘要

采用标准工业相机对盘类零件尺寸进行在线测量,具有成本低、效率高、通用性好等优点,但需要克服投影变形和端面倒角对测量的影响。本工作提出了一种基于机器视觉的测量方法来解决上述问题。为了提高测量精度,将盘类零件的下表面确定为校准平面,上表面确定为测量平面。为了减小投影变形和倒角对测量的影响,通过重投影将测量点重建到测量平面上。然后,通过圆几何拟合测量盘类零件的内外径,并根据测量平面位置计算厚度。实验结果表明,该方法只需单张图像即可在线测量盘类零件尺寸,且精度满足通用级盘类零件的要求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/c547778cadc8/pone.0307525.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/4ffdc31070fa/pone.0307525.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/0e3849341647/pone.0307525.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/e226b60dc073/pone.0307525.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/7e6a2f55b216/pone.0307525.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/c547778cadc8/pone.0307525.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/4ffdc31070fa/pone.0307525.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/0e3849341647/pone.0307525.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/e226b60dc073/pone.0307525.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/7e6a2f55b216/pone.0307525.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/100d/11271902/c547778cadc8/pone.0307525.g005.jpg

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本文引用的文献

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2
Shaft Diameter Measurement Using Structured Light Vision.基于结构光视觉的轴直径测量
Sensors (Basel). 2015 Aug 12;15(8):19750-67. doi: 10.3390/s150819750.
3
Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique.基于改进模板匹配技术的螺旋CT图像中肺结节的自动检测
IEEE Trans Med Imaging. 2001 Jul;20(7):595-604. doi: 10.1109/42.932744.