摘要
针对目前摆线轮检测过程中存在的采集信息量少、测量速度慢等问题,提出了基于机器视觉的综合测量方法。根据摆线轮的测量精度要求,搭建了视觉检测硬件系统;沿粗边缘切向窗口拟合Facet灰度曲面,利用边缘的连续曲面特征,确定亚像素坐标点,利用量块检测定位精度为0.2 pixel;经像素当量标定、光强补偿和坐标变换,得到物理坐标系下摆线轮的亚像素齿廓;将其和三坐标测量法测得的摆线轮廓形对比,得到的摆线轮廓形之差为10μm;根据摆线轮的齿廓方程,采用直角坐标和极坐标相结合方法,建立摆线轮误差计算模型,计算出摆线轮齿廓偏差和齿距偏差;同时评价摆线轮中心孔和2个曲柄轴孔的直径,得出齿廓偏差与极角的关系,为摆线轮的加工工艺改进和RV减速器传动性能分析提供依据。以上整个测量过程时间约为16 s。
In order to solve the problems of less information acquisition and slow measurement speed in cycloid gear detection,a comprehensive measurement method based on machine vision is proposed.According to the measurement accuracy requirements of cycloid gear,the visual detection hardware system is built.Fitting Facet gray surface along edge tangential window,the sub-pixel coordinate points are determined by using edge continuous surface features,and the positioning accuracy is 0.2 pixel by measuring block detection.By pixel equivalent calibration,light intensity compensation and coordinate transformation,the sub-pixel tooth profile of cycloid gear is obtained in physical coordinate system.Compared with the cycloid profile measured by CMM,the difference of cycloid profile obtained is 10μm.According to the tooth profile equation of cycloid gear,the error calculation model of cycloid gear is established by combining rectangular coordinates and polar coordinates,and the tooth profile deviation and tooth pitch deviation are calculated.At the same time,the diameter of the center hole and the two crankshaft holes of cycloid gear are evaluated,and the relationship between tooth profile deviation and polar angle is obtained,which provides the basis for improving the processing technology of cycloid gear and analyzing the transmission performance of RV reducer.The whole measurement process takes about 16 s.
作者
尹婉婉
赵文辉
张静
YIN Wan-wan;ZHAO Wen-hui;ZHANG Jing(School of Mechanical Engineering,Shenyang University of Technology,Shenyang,Liaoning 110870,China)
出处
《计量学报》
CSCD
北大核心
2023年第6期844-851,共8页
Acta Metrologica Sinica
基金
国家自然科学基金(51975386)
辽宁省工业攻关及产业化指导计划(2019JH810100067)。
关键词
计量学
摆线轮
综合测量
机器视觉
亚像素边缘检测
Facet改进算法
齿廓偏差
齿距偏差
metrology
cycloidal gear
comprehensive measurement
machine vision
sub-pixel edge detection
Facet improved algorithm
tooth profile deviation
pitch deviation
