钢轨全轮廓线结构光双目视觉测量系统标定
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摘要
线结构光视觉测量技术因非接触和精度高的特点被用于钢轨磨耗测量。为解决钢轨断面全轮廓测量和线结构光测量系统现场标定困难的问题,提出了一种基于自由平面靶标的线结构光双目现场标定方法。首先,基于线结构光双目视觉测量模型搭建测量系统,分别采集两侧摄像机公共视角下任意位置的不含和包含线结构光的棋盘格平面图像;然后,采用棋盘格平面标定法获取两侧摄像机内部参数。利用线结构光平面与不同位置标定板相交产生的特征点拟合出线结构光平面在两侧摄像机坐标系中的平面方程,采用罗德里格斯变换原理求解出线结构光平面与两侧摄像机的外部参数;最后,结合摄像机内部参数和线结构光平面与摄像机外部参数实现钢轨全轮廓测量,并进行现场测试。试验结果表明,相机内参数标定误差约为0.03 pixel,结构光平面拟合度达0.999,钢轨断面全轮廓总测量偏差为0.54 mm,满足测量精度要求。
The measurement technology of line structured light vision is utilized for the rail wear measurement due to its non-contact and high precision features. The measurement of rail full profile and field calibration of line structured light visual measurement system are two typical problems. To enhance its performance, a binocular calibration method of line structured light based on free plane targets is proposed for field application. Firstly, the vision measurement system is established based on line structured light binocular visual measurement model. The chessboard images containing line structured light and the chessboard images without line structured light at any positions in the public viewing angle of both sides of the camera are collected respectively. Then, the internal parameters of both sides of the camera are obtained by using the chessboard plane calibration method. The feature points which are generated by intersection of line structured light plane and target plane at different positions are used to fit the planar equations of the line structured light plane in both sides of the camera coordinate system. According to the Rodriguez transform principle, the external parameters between the line structured light plane and two cameras are solved. Finally, the internal parameters and the external parameters are utilized to realize the measurement of rail full profile. The field test is also carried out. Experimental results show that the calibration error of the cameras is about 0.03 pixels, the fitting degree of line structured light plane is 0.999, and the total measurement error of rail profile data is 0.54 mm, which meets the requirement of measurement accuracy.
The measurement technology of line structured light vision is utilized for the rail wear measurement due to its non-contact and high precision features. The measurement of rail full profile and field calibration of line structured light visual measurement system are two typical problems. To enhance its performance, a binocular calibration method of line structured light based on free plane targets is proposed for field application. Firstly, the vision measurement system is established based on line structured light binocular visual measurement model. The chessboard images containing line structured light and the chessboard images without line structured light at any positions in the public viewing angle of both sides of the camera are collected respectively. Then, the internal parameters of both sides of the camera are obtained by using the chessboard plane calibration method. The feature points which are generated by intersection of line structured light plane and target plane at different positions are used to fit the planar equations of the line structured light plane in both sides of the camera coordinate system. According to the Rodriguez transform principle, the external parameters between the line structured light plane and two cameras are solved. Finally, the internal parameters and the external parameters are utilized to realize the measurement of rail full profile. The field test is also carried out. Experimental results show that the calibration error of the cameras is about 0.03 pixels, the fitting degree of line structured light plane is 0.999, and the total measurement error of rail profile data is 0.54 mm, which meets the requirement of measurement accuracy.
引文
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[16] 李文涛,王培俊,唐晓敏.钢轨磨损视觉测量的轮廓精确快速提取[J].光学精密工程,2018,26(1):238- 244.LI W T,WANG P J,TANG X M.Accurate and rapid contour extraction of visual measurement for rail wear [J].Optics and Precision Engineering,2018,26(1):238- 244.
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[2] 陈天飞,马孜,吴翔.基于主动视觉标定线结构光传感器中的光平面[J].光学精密工程,2012,20(2):256- 263.CHEN T F,MA Z,WU X.Calibration of light plane in line structured light sensor based on active vision [J].Optics and Precision Engineering,2012,20(2):256- 263.
[3] KIDDEE P,FANG Z,TAN M.A practical and intuitive calibration technique for cross-line structured light [J].Optik,2016,127(20):9582-9602.
[4] 张曦,张健.线结构光标定方法综述[J].激光与光电子学进展,2018,55(2):7-17.ZHANG X,ZHANG J.Summary on calibration method of line-structured light [J].Laser & Optoelectronics Progress,2018,55(2):7-17.
[5] 孙军华,张广军,刘谦哲,等.结构光视觉传感器通用现场标定方法[J].机械工程学报,2009,45(3):174-177.SUN J H,ZHANG G J,LIU Q ZH,et al.Universal method for calibrating structured-light vision sensor on the spot [J].Journal of Mechanical Engineering,2009,45(3):174-177.
[6] 孙军华,王伟华,刘震,等.基于结构光视觉的钢轨磨耗测量方法[J].北京航空航天大学学报,2010,36(9):1026-1029.SUN J H,WANG W H,LIU ZH,et al.Rail wear measurement method based on structured-light vision[J].Journal of Beijing University of Aeronautics and Astronautics,2010,36(9):1026-1029.
[7] 杨凯,余厚云,杨超.基于自由靶标的线结构光视觉测量系统标定研究[J].机电工程,2016,33(9):1066-1070.YANG K,YU H Y,YANG CH.Calibration of line structured-light vision measurement system based on free-traget [J].Journal of Mechnical & Electricail Engineering,2016,33(9):1066-1070.
[8] 占栋,肖建.基于线结构光参考平面的多摄像机灵活标定方法研究[J].仪器仪表学报,2015,36(9):2030- 2036.ZHAN D,XIAO J.Study on the flexible multiple camera calibration approach based on the reference plane emitted by line structured light [J].Chinese Journal of Scientific Instrument,2015,36(9):2030- 2036.
[9] 占栋,于龙,肖建,等.多摄像机结构光大视场测量中全局标定方法研究[J].仪器仪表学报,2015,36(4):903-912.ZHAN D,YU L,XIAO J,et al.Study on multi-cameras and structured-light vision system calibration approach study in large filed view measurement [J].Chinese Journal of Scientific Instrument,2015,36(4):903-912.
[10] ZHANG Z Y.A flexible new technique for camera calibration[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(11):1330-1334.
[11] BROWN D C.Close- range camera calibration [J].Photogrammetric Engineering,1971,37(8):855- 866.
[12] 贺振东,王耀南,刘洁,等.基于背景差分的高铁钢轨表面缺陷图像分割[J].仪器仪表学报,2016,37(3):640- 649.HE ZH D,WANG Y N,LIU J,et al.Background differencing-based high-speed rail surface defect image segmentation [J].Chinese Journal of Scientific Instrument,2016,37(3):640- 649.
[13] ZHANG G J,HE J J,YANG X M.Calibrating camera radial distortion with cross-ratio invariability [J].Optics and Laser Technology,2003,35(6):457- 461.
[14] HOM A.Doubly stochastic matrices and the diagonal of a rotation matrix [J].American Journal of Mathematics,1954,76(3):620- 630.
[15] 陈永冰,李文魁,周岗,等.基于双姿态的高阶罗德里格斯参数姿态估计[J].华中科技大学学报(自然科学版),2017,45(1):82- 86.CHEN Y B,LI W K,ZHOU G,et al.Dual attitude representations based attitude estimation using high order Rodrigues parameter [J].Journal of Huazhong University of Science and Technology (Narual Science Edition),2017,45(1):82- 86.
[16] 李文涛,王培俊,唐晓敏.钢轨磨损视觉测量的轮廓精确快速提取[J].光学精密工程,2018,26(1):238- 244.LI W T,WANG P J,TANG X M.Accurate and rapid contour extraction of visual measurement for rail wear [J].Optics and Precision Engineering,2018,26(1):238- 244.
[17] 中华人民共和国铁道部.高速铁路无砟轨道线路维修规则(试行)[S].北京:中国铁道出版社,2012.The Ministry of Railway for the People′s of China.Railway Transportation.High-speed railway ballastless track maintenance rules (Trial)[S].Beijing:China Railway Press,2012.