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基于机器视觉的活塞杆同轴度误差检测研究

王营营 张学昌 梁涛

王营营, 张学昌, 梁涛. 基于机器视觉的活塞杆同轴度误差检测研究[J]. 机械科学与技术, 2015, 34(12): 1846-1850. doi: 10.13433/j.cnki.1003-8728.2015.1208
引用本文: 王营营, 张学昌, 梁涛. 基于机器视觉的活塞杆同轴度误差检测研究[J]. 机械科学与技术, 2015, 34(12): 1846-1850. doi: 10.13433/j.cnki.1003-8728.2015.1208
Wang Yingying, Zhang Xuechang, Liang Tao. Study on Inspection Method of Coaxial Error for Piston Rod Based on Machine Vision[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(12): 1846-1850. doi: 10.13433/j.cnki.1003-8728.2015.1208
Citation: Wang Yingying, Zhang Xuechang, Liang Tao. Study on Inspection Method of Coaxial Error for Piston Rod Based on Machine Vision[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(12): 1846-1850. doi: 10.13433/j.cnki.1003-8728.2015.1208

基于机器视觉的活塞杆同轴度误差检测研究

doi: 10.13433/j.cnki.1003-8728.2015.1208
基金项目: 

国家自然科学基金项目(51075362)、浙江省自然科学基金项目(Y1100073)及宁波市产业技术创新及成果产业化重点项目(2013B10022)资助

详细信息
    作者简介:

    王营营(1988-),硕士研究生,研究方向为图像测量、机器视觉及应用,wangyingying0503@126.com

    通讯作者:

    张学昌(联系人),教授,zz_zxc123@163.com

Study on Inspection Method of Coaxial Error for Piston Rod Based on Machine Vision

  • 摘要: 针对活塞杆制造过程中同轴度检测出现的精度低,效率低问题,提出了基于机器视觉技术的活塞杆同轴度误差检测方法,并建立了同轴度误差数学模型。采集活塞杆图像并进行边缘特征提取;将基准圆柱表面分解成240个连续的横截面,待测圆柱表面分解成110个连续的横截面;基于最远Voronoi图计算出每个截面的最小外接圆的圆心,并用最小二乘法拟合出活塞杆圆柱面的轴线。以此方法获得基准轴线,求得零件的同轴度误差,并以某型号的活塞杆进行实验分析,结果与三坐标测量机(CMM)测得的误差结果相吻合,表明该方法可以有效、正确地进行同轴度误差的评定。
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出版历程
  • 收稿日期:  2014-03-20
  • 刊出日期:  2015-12-05

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