[1] He BoxiaHe YongXue RongYang Hongfeng,. High-precision automatic measurementof two-dimensional geometric features based on machine vision [J]. Journal of Southeast University (English Edition), 2012, 28 (4): 428-433. [doi:10.3969/j.issn.1003-7985.2012.04.010]
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High-precision automatic measurementof two-dimensional geometric features based on machine vision(
)
二维几何特征的机器视觉高精度自动测量
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 28
- Issue:
- 2012 4
- Page:
- 428-433
- Research Field:
- Automation
- Publishing date:
- 2012-12-30
Info
- Title:
- High-precision automatic measurementof two-dimensional geometric features based on machine vision
- 二维几何特征的机器视觉高精度自动测量
- Author(s):
- He BoxiaHe YongXue RongYang Hongfeng
- School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
- Keywords:
- machine vision; two-dimensional geometric features; high-precision measurement; automatic measurement
- PACS:
- TP216;TH741
- DOI:
- 10.3969/j.issn.1003-7985.2012.04.010
- Abstract:
- To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view(FOV)images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0.03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.
- 为了对零件上二维几何特征进行高精度自动测量, 建立了机器视觉协同测量系统.介绍了系统的硬件组成、功能结构及工作原理, 建立了特征图像坐标与测量空间坐标之间的映射关系, 提出了小视场图像测量路径的规划方法.在被测目标全景图像信息的协同下, 自动采集具有高物面分辨率的小视场序列图像, 自动构造辅助测量特征并提取被测特征的参数.应用该系统测量100 mm的孔距, 结果表明:相对误差的绝对值不超过0.03%;当小视场图像的物面分辨力是大视场图像的16倍时, 小视场图像的测量精度比大视场图像平均提高14倍.故该系统适用于对大尺寸零件上分布的二维复杂几何特征进行高精度自动测量.
References:
[1] Ye Shenghua, Qin Shuren. Development of modern measuring metrological and instrumental technologies[J]. China Measurement & Test, 2009, 35(2):1-6.(in Chinese)
[2] Department of Engineering and Materials Sciences, National Natural Science Foundation of China. Report of the development strategy of mechanical engineering science(2011—2012)[M]. Beijing: Science Press, 2010.(in Chinese)
[3] Weckenmann A, Jiang X, Sommer K D, et al. Multisensor data fusion in dimensional metrology[J]. CIRP Annals-Manufacturing Technology, 2009, 58(2): 701-721.
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[5] Yoon H S, Chung S C. Vision inspection of micro-drilling processes on the machine tool [J]. Transactions of the North American Manufacturing Research Institute of SME, 2004, 32:391-398.
[6] Dutta S, Datta A, Chakladar N D, et al. Detection of tool condition from the turned surface images using an accurate grey level co-occurrence technique[J]. Precision Engineering, 2012, 36(3): 458-466.
[7] Sun T H, Tseng C C, Chen M S, et al. Electric contacts inspection using machine vision [J]. Image and Vision Computing, 2010, 28(6): 890-901.
[8] Quan Yanming, Li Shumei.Fast image mosaic method for large-scale workpiece measurement system[J]. Journal of South China University of Technology: Natural Science Edition, 2011, 39(8):60-65.(in Chinese)
[9] He Boxia, Zhang Zhisheng, Dai Min, et al. A novel method of machine vision measurement based on sequential partial images[C]//Proceedings of the International Conference on Mechanical Engineering and Mechanics. Wuxi, China, 2007:561-566.
[10] Niu Xiaobing, Lin Yuchi, Zhao Meirong, et al. Study on 2-D image connection and its application in geometrical parameters measurement [J]. Journal of Tianjin University: Science and Technology, 2001, 34(3): 396-399.(in Chinese)
[11] He Boxia, Zhang Zhisheng, Dai Min, et al. A high-precision dimension measurement method based on sequential partial images [J]. Optics and Precision Engineering, 2008, 16(2): 367-373.(in Chinese)
[12] Subramanian R, de St Germain H J, Drake S. Integrating a vision system with a coordinate measuring machine to automate the datum alignment process[C]//Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Long Beach, CA, USA, 2005: 655-661.
Memo
- Memo:
-
Biographies: He Boxia(1972—), male, doctor, lecturer, heboxia@163.com; He Yong(1964—), male, doctor, professor, yhe1964@mail.njust.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.51175267), the Natural Science Foundation of Jiangsu Province(No.BK2010481), the Ph.D. Programs Foundation of Ministry of Education of China(No.20113219120004), China Postdoctoral Science Foundation(No.20100481148), the Postdoctoral Science Foundation of Jiangsu Province(No.1001004B).
Citation: He Boxia, He Yong, Xue Rong, et al. High-precision automatic measurement of two-dimensional geometric features based on machine vision[J].Journal of Southeast University(English Edition), 2012, 28(4):428-433.[doi:10.3969/j.issn.1003-7985.2012.04.010]