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浙江大学学报(工学版)
浙江大学学报(工学版)  2020, Vol. 54 Issue (3): 557-565    DOI: 10.3785/j.issn.1008-973X.2020.03.016
计算机技术与图像处理     
采用结构光的大跨度销孔加工精度在线测量
李瑛(),成芳*(),赵志林
浙江大学 生物系统工程与食品科学学院，浙江 杭州 310058
Machining precision online measurement of large span pin hole using structured light
Ying LI(),Fang CHENG*(),Zhi-lin ZHAO
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
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摘要：

设计采用十字线结构光的双相机视觉测量系统，构建由2个高精度工业相机、2个十字激光器和环形光源等组成的图像采集装置. 在传动箱加工现场获取端面销孔图像，提取图像感兴趣区域(ROI)，采用双边滤波进行降噪预处理、二值化和边缘检测；基于改进方向模板法提取2个十字线结构光的中心线. 依据测量系统的设计原理分别测出2个销孔的孔径及其位置度. 结果表明：对于孔径，机器视觉在线测量装置与电子塞规的测量结果的偏差平均值为0.001 mm；对于孔组位置度，机器视觉在线测量装置与三坐标测量仪的测量结果的最大偏差为0.02 mm. 这表明机器视觉在线测量装置能满足加工精度要求和在线实时测量需求.
关键词： 改进方向模板法;  结构光;  大跨度;  加工精度;  在线测量;  机器视觉;  图像处理    
Abstract:

A two-cameras vision measurement system was designed using cross-hair structured light; an image acquisition device was constructed, which consisted of two high-precision industrial cameras, two cross lasers, and a ring light source. The image of the end pinhole at the transmission box processing site was obtained; the image region of interest (ROI) was extracted; bilateral filtering was used for noise reduction preprocessing, binarization and edge detection. The center lines of two cross structured light were extracted based on improved direction template method. According to the design principle of the measuring system, the diameter and position degree of two pin holes were measured, respectively. Results show that, for diameter of pin hole, the average deviation of the measurement results between the machine vision online measureement device and the electronic plug gauge is 0.001 mm; for hole set position degree, the maximum deviation of the measurement results between the machine vision online measuring device and the coordinate measuring device is 0.02 mm. The proposed machine vision online measuring device can meet the requirements of processing accuracy and online real-time measurement.
Key words: improved direction template method    structured light    large span    machining precision    on-line measurement    computer vision    image processing
收稿日期: 2019-01-22 出版日期: 2020-03-05
CLC:  TP 317.4  
基金资助: 国家重点研发计划资助项目（2017YFD0700205）
通讯作者: 成芳     E-mail: 21613053@zju.edu.cn;fcheng@zju.edu.cn
作者简介: 李瑛（1993—），女，硕士生，从事机器视觉测量研究. orcid.org/0000-0002-5489-0921. E-mail： 21613053@zju.edu.cn
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李瑛
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引用本文:

李瑛,成芳,赵志林. 采用结构光的大跨度销孔加工精度在线测量[J]. 浙江大学学报(工学版), 2020, 54(3): 557-565.

Ying LI,Fang CHENG,Zhi-lin ZHAO. Machining precision online measurement of large span pin hole using structured light. Journal of ZheJiang University (Engineering Science), 2020, 54(3): 557-565.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2020.03.016    或    http://www.zjujournals.com/eng/CN/Y2020/V54/I3/557

图 1  传动箱端面销孔尺寸和加工精度要求
图 2  传动箱端面销孔加工精度在线测量系统示意图
图 3  销孔位置度测量原理图
图 4  在线测量系统采集到的传动箱端面销孔原始图像
算法 MSE PSNR
均值滤波 28.504 6 33.581 7
中值滤波 48.375 2 31.284 6
高斯滤波 22.150 7 34.676 9
双边滤波 11.357 5 37.578 0
表 1  4种滤波算法的滤波效果对比
图 5  采用双边滤波后得到的图像和原图的对比
图 6  销孔和结构光图像的感兴趣区域提取
图 7  销孔和结构光图像的直方图与二值化图（反色图像）
图 8  采用Canny算法得到的销孔边缘检测效果图 (反色图像)
图 9  采用霍夫梯度法得到的销孔边缘检测效果图 (反色图像)
图 10  采用形态学细化算法与改进方向模板算法的中心线提取结果对比 (反色图像)
图 11  传动箱加工现场端面销孔加工精度在线测量
mm
测量方法 D1 D2 W H
视觉测量系统 14.957 14.972 40.019 329.988
三坐标测量仪 14.958 14.970 40.008 330.008
表 2  机器视觉在线测量系统与三坐标测量仪的销孔加工质量测量结果对比
图 12  结构光中心线和销孔边缘提取效果图 (反色图像)
mm
箱体编号 视觉测量 电子塞规 ${\delta_1}$
3026181128001 14.963 14.964 0.001
3026181128002 14.960 14.961 0.001
3026181128003 14.967 14.965 0.002
3026181128004 14.970 14.970 0
3026181129001 14.963 14.963 0
3026181129002 14.961 14.960 0.001
3026181129003 14.970 14.965 0.005
3026181129004 14.967 14.966 0.001
表 3  机器视觉在线测量系统与电子塞规的销孔直径测量结果对比
mm
箱体编号 H W
3026181128001 40.019 329.988
3026181128002 39.982 330.000
3026181128003 40.011 329.980
3026181128004 40.008 329.979
3026181129001 40.011 329.971
3026181129002 39.986 330.021
3026181129003 39.993 329.988
3026181129004 39.989 330.017
表 4  机器视觉在线测量系统的位置度测量结果
mm
测量次数 D1 $\delta_2 $ 测量次数 D1 $\delta_2 $
　注：电子塞规对箱体编号为3026181129001的孔径的测量结果为14.963 mm.
1 14.963 0 5 14.963 0
2 14.963 0 6 14.964 0.001
3 14.963 0 7 14.965 0.002
4 14.964 0.001 8 14.964 0
表 5  机器视觉在线测量系统的孔径重复性测量结果
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