影像测量仪自动定位方法研究
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摘要
影像测量仪在工业测量等领域中,尤其是精密平面类零件的高精度测量方面具有广泛的应用。当测量满台零件时,传统影像测量仪需人工手动控制平台移动达到测量位置,导致测量时间延长、效率低。以通用的影像测量仪为实验平台,采用双目视觉系统进行测量,通过大视野相机将特征物从平台任意位置移动到小视野相机视野范围内,并利用小视野进行位置矫正,以达到精确定位。实验结果表明,该方法能有效地将大视野范围内任一特征点精确移动到小视野图像中心。最后,提出一种影像测量仪薄板类零件自动定位方法,实验证明该方法能有效降低测量时长,特征点粗定位误差在±0.05 mm以内。
Image measuring instrument has been widely used in the field of industrial measurement, especially in the measurement of precision planar parts. When measuring a full set of parts, the traditional image measuring instrument needs to manually control the platform movement to reach the measuring position, which leads to prolonged measurement time and low efficiency. In this paper, a universal image measurement instrument is used as the experimental platform. The feature is moved from any position of the platform to a small field of vision through a large field of vision in the way of continuous use of the camera of large and small field of vision, which is corrected by using the small field of vision to achieve precise positioning and optimize the measurement time. The experimental results show that this method can effectively move any feature point within the range of large field of vision to the center of small field of image. Finally, an automatic positioning method for thin sheet parts of the image measuring instrument is proposed. The experiment proves that this method can effectively reduce the measurement time and the movement error of feature points is within 0.05 mm.
Image measuring instrument has been widely used in the field of industrial measurement, especially in the measurement of precision planar parts. When measuring a full set of parts, the traditional image measuring instrument needs to manually control the platform movement to reach the measuring position, which leads to prolonged measurement time and low efficiency. In this paper, a universal image measurement instrument is used as the experimental platform. The feature is moved from any position of the platform to a small field of vision through a large field of vision in the way of continuous use of the camera of large and small field of vision, which is corrected by using the small field of vision to achieve precise positioning and optimize the measurement time. The experimental results show that this method can effectively move any feature point within the range of large field of vision to the center of small field of image. Finally, an automatic positioning method for thin sheet parts of the image measuring instrument is proposed. The experiment proves that this method can effectively reduce the measurement time and the movement error of feature points is within 0.05 mm.
引文
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[14] 敖荟兰,马宏权,周江秀,等.影像测量仪误差分析及控制[J].印制电路信息,2018,26(4):25-30.
[15] 宋丹,刘金国,吴国栋.基于蒙特卡罗法的测绘相机标定误差分析[J].光电子技术,2008,28(3):177-179,183.
[2] 邓小峰.基于机器视觉的零件识别和测量系统研究[D].南京:南京航空航天大学,2014.
[3] 郭小刚,杜文华,曾志强,等.影像测量仪背光源强度影响及误差补偿技术研究[J].组合机床与自动化加工技术,2018,(3):128-130.
[4] 高如新,朱烜甫.基于ORB算法的双目视觉定位[J].电子测量技术,2017,40(4):142-145.
[5] 高飞,葛一粟,汪韬,等.基于空间平面约束的视觉定位模型研究[J].仪器仪表学报,2018,39(7):183-190.
[6] 李康平,李曼雪,郭建军.流光溢彩于数码之间——专业数码相机选型指南[J].中国计算机用户,1999,Z1:43-44,46-47.
[7] 陈曼龙,侯东明.影像测量仪快速标定方法[J].现代制造工程,2017,(8):126-130,140.
[8] 王卫文,周进,张伟丽,等.长距离外参数标定误差分析[J].光电工程,2015,42(11):13-17.
[9] 王晓飞,裘祖荣,杨聪,等.基于影像测量仪的试验筛自动测量方法[J].数据采集与处理,2013,28(2):257-260.
[10] 张俊勇,伍世虔,陈彬,等.基于双目视觉的零件多尺寸在线测量系统[J].仪表技术与传感器,2018,(10):75-80.
[11] 谷凤伟,高宏伟,姜月秋.一种简易的单目视觉位姿测量方法研究[J].光电技术应用,2018,33(4):64-70.
[12] 刘春朋,施宝酉,季清华.基于工业视觉的精整工件智能检测与自动定位系统[J].机械设计,2018,S1:322-325.
[13] 王小章,陈志军,李剑锋.影像测量仪的测量误差研究[J].机床与液压,2009,37(11):117-119.
[14] 敖荟兰,马宏权,周江秀,等.影像测量仪误差分析及控制[J].印制电路信息,2018,26(4):25-30.
[15] 宋丹,刘金国,吴国栋.基于蒙特卡罗法的测绘相机标定误差分析[J].光电子技术,2008,28(3):177-179,183.