基于投影散斑的结构表面形貌测量
|
摘要
结构形貌测量具有重要的工程应用价值。设计了基于投影散斑的结构表面形貌测量方案,结合双目立体视觉标定、散斑特征匹配、三维重建等关键技术,搭建了测量系统,并用该系统测量了典型结构表面的形貌点云数据,最后将测得的点云数据与结构的CAD(computer aided design)模型进行配准,评估了测量方法误差,验证了该方法的准确性。结果表明,投影散班形貌测量方法可以实现结构表面形貌的高精度测量,其最大误差为0.2 mm。
The measurement of structural topography has its important value in engineering development and applications. A program of structural surface topography measurement based on projection speckle is designed. A measurement system is established which applies the following key technologies: calibration of binocular stereo vision,speckle feature match and three-dimensional reconstruction. In addition,the spatial points cloud data of typical structural surface topography is measured using this system. Finally,the measured points cloud data is registration with CAD( computer aided design) model of the same structures,from which the error of measurement method is evaluated,and hence the accuracy of the method is verified. The results indicate that the projection speckle measurement method can measure structural surface topography with high precision,in which the maximum error is0. 2 mm in current case.
The measurement of structural topography has its important value in engineering development and applications. A program of structural surface topography measurement based on projection speckle is designed. A measurement system is established which applies the following key technologies: calibration of binocular stereo vision,speckle feature match and three-dimensional reconstruction. In addition,the spatial points cloud data of typical structural surface topography is measured using this system. Finally,the measured points cloud data is registration with CAD( computer aided design) model of the same structures,from which the error of measurement method is evaluated,and hence the accuracy of the method is verified. The results indicate that the projection speckle measurement method can measure structural surface topography with high precision,in which the maximum error is0. 2 mm in current case.
引文
1于起峰,尚洋.摄像测量学原理与应用研究.北京:科学出版社,2009Yu Qifeng,Shang Yang.Videometrics principles and researches.Beijing:Science Press,2009
2刘胜兰,罗志光,谭高山,等.飞机复杂装配部件三维数字化综合测量与评估方法.航空学报,2013;34(2):409-418Liu Shenglan,Luo Zhiguang,Tan Gaoshan,et al.3D measurement and quality evaluation for complex aircraft assemblies.Acta Aeronautica et Astronautica Sinica,2013;34(2):409-418
3谭启蒙.基于视觉定位跟踪的大型机械部件数字化对接关键技术研究.北京:北京邮电大学,2012Tan Qimeng.Research on key technologies of digital joining largescale mechanical components based on visual positioning and tracking.Beijing:Beijing University of Posts and Telecommunications,2012
4 Bruck H A,Mc Neill S R,Sutton M A,et al.Digital image correlation using Newton-Raphson method of partial differential correction.Experimental Mechanics,1989;29(3):261-267
5 Vendroux G,Knauss W.Submicron deformation field measurements:part 2.Improved digital image correlation.Experimental Mechanics,1998;38(2):86-92
6 Pan B,Qian K,Xie H,et al.Two-dimensional digital image correlation for in-plane displacement and strain measurement:A review.Measurement Science and Technology,2009;20(6):152-154
7 Pan B,Li K,Tong W.Fast,robust and accurate digital image correlation calculation without redundant computations.Experimental Mechanics,2013;53(7):1277-1289
8杭超,杨广,李玉龙,等.数字图像相关方法在焊缝材料力学性能测试中的应用.航空学报,2013;34(10):2372-2382Hang Chao,Yang Guang,Li Yulong,et al.Application of digital image correction method to test of mechanical properties for weld materials.Acta Aeronautica et Astronautica Sinica,2013;34(10):2372-2382
9 Hartley R,Zisserman A.Multiple view geometry in computer vision.2nd ed.London:Cambridge University Press,2000
10 Sutton M A,Orteu J J,Schreier H W.Image correlation for shape,motion and deformation measurements:Basic concepts,theory and applications.New York:Springer,2009
11 Zhang Z.Flexible camera calibration by viewing a plane from unknown orientations.In Proceedings 7th International Conference on Computer Vision.New York:Institute of Electrical and Electronics Engineers,1999:666-673
12 Zhang Z.Iterative point matching for registration of freeform curves and surfaces.International Journal of Computer Vision,1994;13(2):119-152
2刘胜兰,罗志光,谭高山,等.飞机复杂装配部件三维数字化综合测量与评估方法.航空学报,2013;34(2):409-418Liu Shenglan,Luo Zhiguang,Tan Gaoshan,et al.3D measurement and quality evaluation for complex aircraft assemblies.Acta Aeronautica et Astronautica Sinica,2013;34(2):409-418
3谭启蒙.基于视觉定位跟踪的大型机械部件数字化对接关键技术研究.北京:北京邮电大学,2012Tan Qimeng.Research on key technologies of digital joining largescale mechanical components based on visual positioning and tracking.Beijing:Beijing University of Posts and Telecommunications,2012
4 Bruck H A,Mc Neill S R,Sutton M A,et al.Digital image correlation using Newton-Raphson method of partial differential correction.Experimental Mechanics,1989;29(3):261-267
5 Vendroux G,Knauss W.Submicron deformation field measurements:part 2.Improved digital image correlation.Experimental Mechanics,1998;38(2):86-92
6 Pan B,Qian K,Xie H,et al.Two-dimensional digital image correlation for in-plane displacement and strain measurement:A review.Measurement Science and Technology,2009;20(6):152-154
7 Pan B,Li K,Tong W.Fast,robust and accurate digital image correlation calculation without redundant computations.Experimental Mechanics,2013;53(7):1277-1289
8杭超,杨广,李玉龙,等.数字图像相关方法在焊缝材料力学性能测试中的应用.航空学报,2013;34(10):2372-2382Hang Chao,Yang Guang,Li Yulong,et al.Application of digital image correction method to test of mechanical properties for weld materials.Acta Aeronautica et Astronautica Sinica,2013;34(10):2372-2382
9 Hartley R,Zisserman A.Multiple view geometry in computer vision.2nd ed.London:Cambridge University Press,2000
10 Sutton M A,Orteu J J,Schreier H W.Image correlation for shape,motion and deformation measurements:Basic concepts,theory and applications.New York:Springer,2009
11 Zhang Z.Flexible camera calibration by viewing a plane from unknown orientations.In Proceedings 7th International Conference on Computer Vision.New York:Institute of Electrical and Electronics Engineers,1999:666-673
12 Zhang Z.Iterative point matching for registration of freeform curves and surfaces.International Journal of Computer Vision,1994;13(2):119-152