Volume 46 Issue 3
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Liu Wei, Gao Peng, Zhang Yang, Yang Fan, Li Xiaodong, Lan Zhiguang, Jia Zhenyuan, Gao Hang. High-precision measurement method for 3D shape of large-scale parts[J]. Infrared and Laser Engineering, 2017, 46(3): 317003-0317003(9). doi: 10.3788/IRLA201746.0317003
Citation: Liu Wei, Gao Peng, Zhang Yang, Yang Fan, Li Xiaodong, Lan Zhiguang, Jia Zhenyuan, Gao Hang. High-precision measurement method for 3D shape of large-scale parts[J]. Infrared and Laser Engineering, 2017, 46(3): 317003-0317003(9). doi: 10.3788/IRLA201746.0317003
shu

High-precision measurement method for 3D shape of large-scale parts

doi: 10.3788/IRLA201746.0317003
  • 1.

    College of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China

  • Received Date: 2016-07-05
  • Rev Recd Date: 2016-08-10
  • Publish Date: 2017-03-25
  • The measurement method based on laser-aided machine vision has been widely used in 3D shape measurement for large-scale components and parts at present. To solve the problem of the inaccurate extraction for components boundaries, a high-precision method of 3D shape measurement for large-scale parts was proposed in this paper. Firstly, an adaptive light stripe locating method based on time flow was proposed according to the sequence of acquiring images, by which the region of the light stripe can be located in real time. Next, a boundary detection method based on light stripe mutations was presented to acquire the row or column coordinates of the object boundaries in the light stripe. Then the coordinates of the boundaries can be determined precisely combined with the extraction results of light stripe centers. And the effective light stripe centers for measurement within the two determined boundary feature points can be retained. At last, the extracted light stripe centers were matched and reconstructed to accomplish 3D shape measurement. Experiment results show that the measurement accuracy of this method reaches 0.06 mm and precise boundary information of objects can be acquired. The cost of computation is also reduced greatly. Thus, the proposed method can satisfy the measurement requirements of high precision and rapid speed.
  • [1] Fu Shuai, Zhang Liyan, Ye Nan, et al. Light pen based on-site vision measurement system for large workpieces[J]. Chinese Journal of Scientific Instrument, 2015, 36(2):430-438. (in Chinese)富帅, 张丽艳, 叶南, 等. 面向大型工件现场测量的光笔式视觉测量系统[J]. 仪器仪表学报, 2015, 36(2):430-438.
    [2] Zhao Sihong, Lu Yabing, Chen Xiaoxu, et al. Realization of real-time automatic target reporting system for simulant airborneweapon attacking over ground[J]. Infrared and Laser Engineering, 2014, 43(S1):78-82. (in Chinese)赵思宏, 陆亚兵, 陈晓旭, 等. 航空武器对地模拟攻击实时自动报靶系统的实现[J]. 红外与激光工程, 2014, 43(S1):78-82.
    [3] Li Hui, Zhang Linxuan, Xiao Tianyuan, et al. Real-time control for CPS of digital airplane assembly with robust H-infinity theory[J]. Tsinghua Science and Technology, 2015, 20(4):376-384.
    [4] Bai Suqin, Shi Jinlong, Qian Qiang, et al. 3D measurement of large steel plates based on the integration of computer vision and laser technology[J]. Journal of Optoelctronics.Laser, 2015(3):581-585. (in Chinese)白素琴, 史金龙, 钱强, 等. 视觉与激光相融合的大尺度钢板三维测量[J]. 光电子激光, 2015(3):581-585.
    [5] Gao Yuhan, An Zhiyong, Wang Jinsong, et al. Precision measurement technology of 3D surfaces[J]. Infrared and Laser Engineering, 2011, 40(11):2261-2264. (in Chinese)高蠫含, 安志勇, 王劲松, 等. 三维面型精密测量技术[J]. 红外与激光工程, 2011, 40(11):2261-2264.
    [6] Zhou Na, An Zhiyong, Li Yonghao. Large-sized three-dimensional profile measurement technology based on laser radar[J]. Infrared and Laser Engineering, 2011, 40(12):2465-2468. (in Chinese)周娜, 安志勇, 李咏豪. 采用激光雷达的三维形貌测量技术[J]. 红外与激光工程, 2011, 40(12):2465-2468.
    [7] Cai Huaiyu, Feng Zhaodong, Huang Zhanhua. Centerline extraction of structured light stripe based on principal component analysis[J]. Chinese Journal of Lasers, 2015(3):1-6. (in Chinese)蔡怀宇, 冯召东, 黄战华. 基于主成分分析的结构光条纹中心提取方法[J]. 中国激光, 2015(3):1-6.
    [8] Nakia H, Iwai D, Sato K. 3D shape measurement using fixed camera and handheld laser scanner[J]. Ipsj Sig Notes Cvim, 2008, 1536-1539.
    [9] Ruben U, Julio M, Daniel F G. Fast and robust laser stripe extraction for 3D reconstruction in industrial environments[J]. Machine Vision and Applications, 2012, 23:179-796.
    [10] Zhang Yixin, Wang Shun, Zhang Xuping. Defocused blur image restoration in large scale 3D vision measurement[J]. Chinese Journal of Scientific Instrument, 2010, 31(12):2748-2753. (in Chinese)张益昕, 王顺, 张旭苹. 大尺度三维视觉测量中的离焦模糊图像恢复[J]. 仪器仪表学报, 2010, 31(12):2748-2753.
    [11] Feng Ping, Wei Zhenzhong. Light probe based large FOV 3D vision measurement system[J]. Opt Precision Eng, 2013, 21(9):2217-2224. (in Chinese)冯萍, 魏振忠. 光笔式大视场三维视觉测量系统[J].光学精密工程, 2013, 21(9):2217-2224.
    [12] Sun Lina. Research on the methods of sub-pixel extraction and tracking of laser curve in inspection system of vehicle profile[D]. Changchun:Jilin University, 2015:39-55. (in Chinese)孙丽娜. 汽车形貌检测系统的光条亚像素提取及跟踪方法的研究[D]. 长春:吉林大学, 2015:39-55.
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High-precision measurement method for 3D shape of large-scale parts

doi: 10.3788/IRLA201746.0317003
  • 1. College of Mechanical Engineering,Dalian University of Technology,Dalian 116024,China
  • Received Date: 2016-07-05
  • Rev Recd Date: 2016-08-10
  • Publish Date: 2017-03-25

Abstract: The measurement method based on laser-aided machine vision has been widely used in 3D shape measurement for large-scale components and parts at present. To solve the problem of the inaccurate extraction for components boundaries, a high-precision method of 3D shape measurement for large-scale parts was proposed in this paper. Firstly, an adaptive light stripe locating method based on time flow was proposed according to the sequence of acquiring images, by which the region of the light stripe can be located in real time. Next, a boundary detection method based on light stripe mutations was presented to acquire the row or column coordinates of the object boundaries in the light stripe. Then the coordinates of the boundaries can be determined precisely combined with the extraction results of light stripe centers. And the effective light stripe centers for measurement within the two determined boundary feature points can be retained. At last, the extracted light stripe centers were matched and reconstructed to accomplish 3D shape measurement. Experiment results show that the measurement accuracy of this method reaches 0.06 mm and precise boundary information of objects can be acquired. The cost of computation is also reduced greatly. Thus, the proposed method can satisfy the measurement requirements of high precision and rapid speed.

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