程淼,陈松,徐进文,张霄烽,陈燕,韩冰.基于廓形识别的弯管内表面精密磨削试验研究[J].表面技术,2021,50(11):372-382.
CHENG Miao,CHEN Song,XU Jin-wen,ZHANG Xiao-feng,CHEN Yan,HAN Bing.Experimental Research on Precision Grinding of Inner Surface of Elbow Based on Profile Recognition[J].Surface Technology,2021,50(11):372-382
基于廓形识别的弯管内表面精密磨削试验研究
Experimental Research on Precision Grinding of Inner Surface of Elbow Based on Profile Recognition
投稿时间:2021-01-05  修订日期:2021-06-07
DOI:10.16490/j.cnki.issn.1001-3660.2021.11.040
中文关键词:  磁粒研磨  弯管  廓形中线  研磨轨迹  受力状态  研磨效率
英文关键词:magnetic abrasive finishing  elbow  profile centerline  grinding track  force state  grinding efficiency
基金项目:辽宁省教育厅项目(2020FWDF07,2020FWDF05);辽宁省自然科学基金(2019ZD0275)
作者单位
程淼 辽宁科技大学 机械工程与自动化学院,辽宁 鞍山 114051 
陈松 辽宁科技大学 机械工程与自动化学院,辽宁 鞍山 114051 
徐进文 辽宁科技大学 机械工程与自动化学院,辽宁 鞍山 114051 
张霄烽 辽宁科技大学 机械工程与自动化学院,辽宁 鞍山 114051 
陈燕 辽宁科技大学 机械工程与自动化学院,辽宁 鞍山 114051 
韩冰 辽宁科技大学 机械工程与自动化学院,辽宁 鞍山 114051 
AuthorInstitution
CHENG Miao School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, China 
CHEN Song School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, China 
XU Jin-wen School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, China 
ZHANG Xiao-feng School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, China 
CHEN Yan School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, China 
HAN Bing School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, China 
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中文摘要:
      目的 解决弯管内表面磁粒研磨工艺中手动采点所产生的随机误差大、研磨间隙无法保证以及位姿不准确等问题。方法 结合工业机器人与工业相机,设计并实现了弯管廓形中线的快速获取及研磨位姿计算的工艺方法。首先,分析了弯管内表面磁粒研磨工艺的基本原理,根据研磨过程中单颗磨粒的受力状态以及对研磨区域的磁场模拟,得出影响研磨压力的主要工艺参数;其次,利用工业相机获取弯管图像,通过图像处理算法,得到弯管的廓形中线;最后,将中线上的坐标点进行坐标转换、拟合、离散,并结合磁粒研磨工艺特点,计算出研磨过程中机器人的运动位姿,同时与手动采点法的试验结果进行对比分析,以检验该方法的可行性。结果 廓形识别法提取出的研磨轨迹较为平滑,用时少,能够保持稳定的研磨间隙且更贴近实际弯管中线。在相同试验条件下,对具有180°转角的铜弯管进行研磨,经廓形识别方法研磨60 min后,表面粗糙度Ra由原始的0.854 μm降至0.236 μm,达到最佳。表面划痕细致且均匀,无过磨、深度划痕等缺陷,平均研磨速率比手动采点法提高了约35.8%,粗糙度的下降率提高了约3.8%。结论 在弯管内表面磁粒研磨过程中,廓形识别法能快速准确地获取弯管廓形中线并计算机器人研磨位姿,在保持正确研磨位姿的同时,能够维持稳定的研磨间隙,可有效提高弯管内表面磁粒研磨效率及表面质量。
英文摘要:
      The work aims to solve the problems of large random errors caused by manual point sampling in the magnetic abrasive finishing process of the inner surface of the elbow, the grinding gap cannot be guaranteed, and the inaccurate pose. Combined with an industrial robot and an industrial camera, a process method for quickly obtaining the centerline of the curved pipe profile and calculating the grinding pose was designed and realized. First, the basic principle of the magnetic abrasive finishing process on the inner surface of the elbow is analyzed. According to the force state of a single abrasive particle during the grinding process and the magnetic field simulation of the grinding area, the main process parameters that affect the grinding pressure are obtained. Secondly, use the industrial camera to obtain the image of the bent pipe, and obtain the profile centerline of the bent pipe through the image processing algorithm. Finally, the coordinate points on the center line are converted, fitted, and discrete, and combined with the characteristics of the magnetic abrasive finishing process to calculate the movement poses of the robot during the grinding process. At the same time, the test results of this method and the manual point collection method are compared and analyzed, to test the feasibility of this method. The finishing trajectory extracted by the profile recognition method is smoother, takes less time, can maintain a stable finishing gap and is closer to the actual center line of the bend. Under the same test conditions, copper elbow with 180° corner was ground. After 60 minutes of grinding by the profile recognition method, the surface roughness Ra decreased from the original 0.854 μm to 0.236 μm, reaching the best effect. The scratches on the surface are dense and uniform, without defects such as over-grinding and deep scratches. The average speed is about 35.8% higher than the manual point-taking method, and the roughness reduction rate is enhanced by about 3.8%. The application of the profile recognition method in the magnetic abrasive finishing process of the inner surface of the elbow can quickly and accurately obtain the profile centerline of the elbow and calculate the grinding pose of the robot. It can maintain a stable grinding gap while maintaining the correct grinding position, which can effectively improve the grinding efficiency and surface quality of the magnetic abrasive on the inner surface of the elbow.
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