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基于机器视觉的曲轴圆度误差评定
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山东省自然科学基金项目(2021ME160);山东省研究生教育质量提升计划项目 (SDYAL20127);山东省科技型中小企业创新能力提升工程项目(2022TSGC1164)


Evaluation of Crankshaft Roundness Error Based on Machine Vision
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    摘要:

    针对曲轴圆度测量效率低、稳定性差等现状,提出一种基于机器视觉的测量方法。首先,搭建视觉平台采集图像;其次,进行预图像处理并运用亚像素手段提高边缘精度,经三维重构复现圆周;然后,提出曲轴圆度误差视觉评定方案,并通过倾斜校正和回转误差补偿提高测量精度;最后,进行曲轴圆度误差测量对比实验。结果表明:视觉评定结果与三坐标测量机测量结果相比均值误差为6 μm,可实现曲轴圆度误差测量,且更加稳定。

    Abstract:

    Aiming at the low efficiency and poor stability of crankshaft roundness measurement,a measurement method based on machine vision was proposed.A vision platform was built to collect images;image preprocessing and sub-pixel method were used to improve the edge accuracy,and the circle was reconstructed by 3D reconstruction.Then,the visual evaluation scheme of crankshaft roundness error was proposed,and the measurement accuracy was improved by tilt correction and rotation error compensation.Finally,the contrast experiment of crankshaft roundness error measurement was carried out.The results show that the average error of visual evaluation results is 6 μm.The roundness error measurement of the crankshaft can be realized and more stable.

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李长安,张丹,隋文涛,逯海滨,窦亚萍.基于机器视觉的曲轴圆度误差评定[J].机床与液压,2023,51(20):77-80.
LI Changan, ZHANG Dan, SUI Wentao, LU Haibin, DOU Yaping. Evaluation of Crankshaft Roundness Error Based on Machine Vision[J]. Machine Tool & Hydraulics,2023,51(20):77-80

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  • 在线发布日期: 2023-11-01
  • 出版日期: 2023-10-28