基于结构光视觉技术的圆柱度测量新方法

doi:10.13229/j.cnki.jdxbgxb201702025

吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (2): 524-529.doi: 10.13229/j.cnki.jdxbgxb201702025

基于结构光视觉技术的圆柱度测量新方法

周晓东^{1, 2}, 张雅超¹, 谭庆昌¹, 张维君³

1.吉林大学机械科学与工程学院, 长春 130022;
2.长春工业大学机电工程学院,长春 130012;
3.空军航空大学飞行器与动力系,长春 130022

收稿日期:2016-08-29 出版日期:2017-03-20 发布日期:2017-03-20
通讯作者: 谭庆昌(1957-),男,教授,博士生导师.研究方向:视觉测量,机械动力学,摩擦学.E-mail:tanqc@jlu.edu.cn
作者简介:周晓东(1974-),男,博士研究生.研究方向:智能检测,视觉测量.E-mail:zhouxiaodong@ccut.edu.cn
基金资助:
国家自然科学基金项目(51405184); 吉林省科技发展计划项目(20160520070JH).

New method of cylindricity measurement based on structured light vision technology

ZHOU Xiao-dong^{1, 2}, ZHANG Ya-chao¹, TAN Qing-chang¹, ZHANG Wei-jun³

1.College of Mechanical Science and Engineering, Jilin University, Changchun 130022, China;
2.School of Mechatronic Engineering, Changchun University of Technology,Changchun 130012,China;
3.Aircarft Dynamic Department,Aviation University of Air Force,Changchun 130022,China

Received:2016-08-29 Online:2017-03-20 Published:2017-03-20

摘要/Abstract

摘要： 针对机器视觉测量轴类零件的圆柱度误差时因使用畸变严重的鱼眼镜头影响测量精度的问题,提出了一种基于结构光视觉技术的圆柱度测量新方法。该方法投射的结构光与被测轴轴线方向近似平行,考虑轴类零件的特征和鱼眼镜头畸变分布的规律,将视场分为多个区域进行畸变修正。给出了结构光分区标定的模型、测量数据的提取及数据转换的方法。通过对标准轴的测量检验了本文方法的可行性和准确性,实验结果表明,直径为27.68 mm、长为300 mm的轴的圆柱度的测量精度为20 μm。该方法不仅满足产品几何技术规范的采样要求,而且具有非接触、高效、在线测量的特点,能为圆柱度的精确评定提供可靠的数据信息。

关键词: 机械学, 机器视觉, 圆柱度, 结构光视觉, 分区标定, 畸变

Abstract: In the measurement of cylindricity errors of shaft parts using machine vision technology, severely distorted fishy lens will influenced the precision. To overcome this problem, a new method is proposed based on structured light vision technology. In this method, the projected structure light is approximate parallel to the direction of the measured axis. The field of view is divided into multi-regions according to the characteristics of the shaft elements and the distribution of the lens distortion, then multi-regions calibration is carried out. The multi-calibration model, the data extraction and data processing methods are given. The feasibility and accuracy of the proposed method are verified by measuring a standard shaft. Results show that the measuring accuracy of a shaft, diameter of 27.68 mm and length of 300 mm, is 20 μm. The method not only satisfies the sampling requirements of geometrical specification, but also has the advantages of non-contact, high efficiency and online measurement, which provides reliable data for cylindricity evaluation.

Key words: computer application, machine vision, cylindricity, structured light vision, multi-regions calibration, distortion

中图分类号:

TH115

周晓东, 张雅超, 谭庆昌, 张维君. 基于结构光视觉技术的圆柱度测量新方法[J]. 吉林大学学报(工学版), 2017, 47(2): 524-529.

ZHOU Xiao-dong, ZHANG Ya-chao, TAN Qing-chang, ZHANG Wei-jun. New method of cylindricity measurement based on structured light vision technology[J]. 吉林大学学报(工学版), 2017, 47(2): 524-529.

参考文献

[1] Dhanish P B. A simple algorithm for evaluation of minimum zone circularity error from coordinate data[J]. International Journal of Machine Tools and Manufacture,2002, 42(14): 1589-1594.
[2] Samuel G L, Shunmugam M S. Evaluation of circularity from coordinate and form data using computational geometric techniques[J]. Precision Engineering,2000, 24(3): 251-263.
[3] Tsukada T, Kanada T, Liu S. Method for the evaluation of form errors of conical tapered parts[J]. Precision Engineering,1988, 10(1): 8-12.
[4] Carr K, Ferreira P. Verification of form tolerances part II: cylindricity and straightness of a median line[J]. Precision Engineering,1995, 17(2): 144-156.
[5] Brown G M, Chen F. Optical methods for shape measurement[J]. Opt Eng,2000,39(1):8-9.
[6] 刘岩. 圆柱工件形位误差非接触智能在线检测技术研究[D]. 长春:吉林大学机械科学与工程学院, 2007:13-20.
Liu Yan. Study on the on-line non-contact and intelligent detection technique of form and position errors of cylindrical workpiece[D]. Changchun:College of Mechanical Science and Engineering,Jilin University,2007: 13-20.
[7] 车佳斯. 零件圆度与圆柱度的图像测量研究[D]. 长春:吉林大学机械科学与工程学院, 2007: 16-17.
Che Jia-si. Research of the mechanical part roundness error and cyclindricity error on the image measurement technology[D]. Changchun:College of Mechanical Science and Engineering,Jilin University,2007: 16-17.
[8] 郑鹏,张琳娜,陈明仪,等. 基于面阵传感技术的圆柱度测量新方法[J]. 机械强度, 2011, 33(5): 771-776.
Zheng Peng, Zhang Lin-na, Chen Ming-yi, et al. Novel method of cylindricity measurement based on area-array sensing technology[J]. Journal of Mechanical Strength, 2011, 33(5): 771-776.
[9] 王喜利. 产品几何技术规范(GPS)国家标准应用指南[M].北京:中国标准出版社, 2010.
[10] 陈会,密保秀,高志强. 基于畸变规律的三维结构光测量系统标定[J]. 光学学报,2013(12): 162-170.
Chen Hui, Mi Bao-xiu, Gao Zhi-qiang. Calibration of 3D structured light measurement system based on the properities of lens distorition[J]. Acta Optica Sinica, 2013(12): 162-170.
[11] Sun Q, Hou Y, Tan Q. A new method of camera calibration based on the segmentation model[J]. Optik-International Journal for Light and Electron Optics,2013, 124(124): 6991-6995.
[12] 孙军华,刘震,张广军,等. 基于柔性立体靶标的摄像机标定[J]. 光学学报, 2009(12): 3433-3439.
Sun Jun-hua, Liu Zhen, Zhang Guang-jun, et al. Camera calibration based on flexible 3D target[J]. Acta Optica Sinica, 2009(12): 3433-3439.
[13] 马鑫, 魏仲慧, 何昕, 等. 三维枪弹痕点云数据处理及特征提取研究[J]. 液晶与显示, 2016, 31(9): 889-896.
Ma Xin, Wei Zhong-hui, He Xin, et al. Processing and feature extraction for three-dimensional bullet point cloud data[J].Chinese Journal of Liquid Crystal and Displays, 2016, 31(9): 889-896.
[14] 田浩南, 张叶. 基于边缘及特征点匹配的立体图像质量评价[J]. 液晶与显示, 2015, 30(4): 666-672.
Tian Hao-nan, Zhang Ye. Quality evaluation of stereo image based on edge and characteristic point matching[J]. Chinese Journal of Liquid Crystal and Displays, 2015, 30(4): 666-672.
[15] 李璐璐,赵文川,伍凡,等. 摄像机标定中的特征点提取算法研究与改进[J]. 光学学报, 2014(5): 171-178.
Li Lu-lu, Zhao Wen-chuan, Wu Fan, et al. Analysis and improvement of characteristic points extraction algorithms in camera calibration[J]. Acta Optica Sinica, 2014(5): 171-178.
[16] More J J. The Levenberg-Marquardt Algorithm, Implementation and Theory[J]. Lecture Notes in Mathematics,1978,630:105-116.

相关文章 15

[1]	刘恩泽,吴文福. 基于机器视觉的农作物表面多特征决策融合病变判断算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1873-1878.
[2]	林金花, 王延杰, 王璐, 姚禹. 全局相机姿态优化下的快速表面重建[J]. 吉林大学学报(工学版), 2018, 48(3): 909-918.
[3]	侯萍萍, 王黎钦, 柏迎村, 彭秋阳, 郝婷. 填脂量对高速电主轴轴承性能的影响[J]. 吉林大学学报(工学版), 2017, 47(2): 518-523.
[4]	张飞, 单忠德, 任永新, 聂军刚, 刘丰. 缸盖缺陷检测系统线阵相机现场标定方法[J]. 吉林大学学报(工学版), 2017, 47(2): 540-545.
[5]	廖静平, 张建富, 郁鼎文, 冯平法. 基于虚拟梯度材料的螺栓结合面建模方法[J]. 吉林大学学报(工学版), 2016, 46(4): 1149-1155.
[6]	孙伟, 李健, 贾师. 硬涂层复合结构非线性刚度及阻尼辨识[J]. 吉林大学学报(工学版), 2016, 46(4): 1156-1162.
[7]	张波,王文军,魏民国,成波. 基于机器视觉的驾驶人使用手持电话行为检测[J]. 吉林大学学报(工学版), 2015, 45(5): 1688-1695.
[8]	张保华, 黄文倩, 李江波, 赵春江, 刘成良, 黄丹枫. 基于I-RELIEF和SVM的畸形马铃薯在线分选[J]. 吉林大学学报(工学版), 2014, 44(6): 1811-1817.
[9]	刘长英¹, 蔡文静¹, 王天皓², 李机智¹, 贾艳梅¹, 宋玉河¹. 汽车连杆裂解槽视觉检测技术[J]. 吉林大学学报(工学版), 2014, 44(4): 1076-1080.
[10]	侯守武, 焦映厚, 陈照波, 李明章. 基于机械导纳理论的方钢结构减振特性[J]. 吉林大学学报(工学版), 2013, 43(05): 1295-1301.
[11]	李成, 朱红红, 铁瑛, 何龙. 单搭胶/螺栓混合连接结构的应力分布与载荷分配[J]. 吉林大学学报(工学版), 2013, 43(04): 933-938.
[12]	万川, 田彦涛, 刘帅师, 陈宏伟. 基于主动机器视觉的人脸跟踪与表情识别系统[J]. 吉林大学学报(工学版), 2013, 43(02): 459-465.
[13]	孔繁森,吴雅夫,李聪. 基于信息熵的设备电气故障诊断复杂性评价[J]. 吉林大学学报(工学版), 2011, 41(03): 697-701.
[14]	杨志军,罗伯特·凯利,陈新,何捷. 基于机构动力学-控制系统协同仿真与优化的凸轮廓线优化设计[J]. 吉林大学学报(工学版), 2011, 41(01): 149-0154.
[15]	赵丁选, 崔玉鑫, 龚捷, 倪涛, 侯敬巍, 赵颖, 王超飞. 基于机器视觉的运动目标跟踪及位置检测方法[J]. 吉林大学学报(工学版), 2010, 40(增刊): 257-0261.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

基于结构光视觉技术的圆柱度测量新方法

New method of cylindricity measurement based on structured light vision technology

PDF (PC)

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0