基于UGII的反求工程数据处理技术研究与系统开发
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摘要
本文针对目前UGII与反求工程系统存在的不足,以Visual Studio.NET 2003为开发工具,开展了UGII反求工程模块的部分研发工作。论文主要完成的研究内容如下:
(1)通过研究UG/Open API接口技术和UDO方法,设计了点云类,创建了点云对象、UDO类及对象,并结合C++纯虚函数技术,成功地将海量数据点以像素点的形式显示在UGII系统的主窗口中;
(2)通过采用WINDOWS API函数和UG/OPEN C API函数获取了UGII的主窗口指针,利用鼠标钩子捕捉鼠标点的屏幕位置,并进一步通过OpenGL API函数将世界坐标系下的点映射到窗口坐标系下,结合多边形内外点的判断算法,在UGII中实现了点云的交互区域分割;
(3)通过研究支持数据动态管理的空间数据结构R-tree,在优选其变种R*-tree作为本课题的点云空间数据结构的基础上,提出了一种在R*-tree中搜索数据点K近邻的算法;
(4)通过研究固定球拟合、坐标转换及数据融合算法,提出了一种基于最小二乘球的多视点云拼合算法,并与UGII系统无缝集成,该算法可快速、精确地对多视点云数据进行对齐与融合;
(5)研究了曲率估算方法和数据精简原则,提出了一种适用于任意类型测量点云的曲率精简算法,将其集成到UGII系统后,实现了对大量密集数据点直接、有效地精简;
(6)通过分析已有散乱数据三角网格剖分算法,制定了候选点有效准则、匹配点查找及优化准则和四种数据更新方法,提出了一种通用的三角网格快速剖分算法——螺旋波扩展法,实现了散乱数据的快速、高质量地三角网格剖分;
(7)实现了四种三角网格后处理算法,包括:内外边界提取、数据分块、网格自适应加密及网格模型抽壳,为快速构建特征线、有限元分析及快速原型奠定了基础。
Since there are some shortcomings in reverse engineering systems and UGII, part of reverse engineeringsystem based on UGII is researched and developed with Visual Studio.NET 2003. The achievements of thispaper are as follows:
(1) With the research of the interface technique about UG/Open API and the UDO method, the pointcloud class is designed, the point cloud object, the UDO class and object are created, and a large number ofpoints are displayed in the main window of UGII as pixel points with the pure virtual functions of the C++.
(2)Through obtaining the main window pointer of UGII by functions of windows API and UG/OPEN CAPI, capturing the mouse coordinates in the screen by setting a mouse hook, and projecting the points of theworld coordinate system by calling OpenGL API functions, a point cloud is partitioned into two regions inUGII based on an algorithm of point in-out polygon test.
(3) With the research of the spatial data structure called R-tree which supports dynamic data-managementand the selection of its variation — R*-tree as the spacial data structure of this project, a searching algorithmof K nearest neighbor points in R*-tree is proposed.
(4) Through researching the algorithms of fitting fixed-sphere, transforming coordinates and dataintegration, the algorithm of registration and integration based on least-square sphere is proposed andintegrated with UGII, which can registrate and integrate multi-view point cloud data rapidly and accurately.
(5) Through researching the algorithm of curvature estimate and the principle of data reduction, the datareduction algorithm based on curvature estimation is proposed and integrated with UGII, which can beapplied to any kind of measured data and reduces the mass and dense points directly and effectively.
(6) Through analyzing several previous algorithms of triangulation for scattered data, and establishing theeffective criterion for candidate points, the search and optimizing criterions for match points and fourmethods of data updating, a universal and fast mesh generation algorithm named helix-wave expandingmethod is proposed, which can generate high-quality triangular mesh quickly.
(7) Four algorithms of mesh postprocessing are realized, including inside and outside boundary extraction,data segment, adaptive mesh refinement and mesh model hollowing, which establish the groundwork forfeature line construction, finite element analysis and rapid prototyping.
(1)通过研究UG/Open API接口技术和UDO方法,设计了点云类,创建了点云对象、UDO类及对象,并结合C++纯虚函数技术,成功地将海量数据点以像素点的形式显示在UGII系统的主窗口中;
(2)通过采用WINDOWS API函数和UG/OPEN C API函数获取了UGII的主窗口指针,利用鼠标钩子捕捉鼠标点的屏幕位置,并进一步通过OpenGL API函数将世界坐标系下的点映射到窗口坐标系下,结合多边形内外点的判断算法,在UGII中实现了点云的交互区域分割;
(3)通过研究支持数据动态管理的空间数据结构R-tree,在优选其变种R*-tree作为本课题的点云空间数据结构的基础上,提出了一种在R*-tree中搜索数据点K近邻的算法;
(4)通过研究固定球拟合、坐标转换及数据融合算法,提出了一种基于最小二乘球的多视点云拼合算法,并与UGII系统无缝集成,该算法可快速、精确地对多视点云数据进行对齐与融合;
(5)研究了曲率估算方法和数据精简原则,提出了一种适用于任意类型测量点云的曲率精简算法,将其集成到UGII系统后,实现了对大量密集数据点直接、有效地精简;
(6)通过分析已有散乱数据三角网格剖分算法,制定了候选点有效准则、匹配点查找及优化准则和四种数据更新方法,提出了一种通用的三角网格快速剖分算法——螺旋波扩展法,实现了散乱数据的快速、高质量地三角网格剖分;
(7)实现了四种三角网格后处理算法,包括:内外边界提取、数据分块、网格自适应加密及网格模型抽壳,为快速构建特征线、有限元分析及快速原型奠定了基础。
Since there are some shortcomings in reverse engineering systems and UGII, part of reverse engineeringsystem based on UGII is researched and developed with Visual Studio.NET 2003. The achievements of thispaper are as follows:
(1) With the research of the interface technique about UG/Open API and the UDO method, the pointcloud class is designed, the point cloud object, the UDO class and object are created, and a large number ofpoints are displayed in the main window of UGII as pixel points with the pure virtual functions of the C++.
(2)Through obtaining the main window pointer of UGII by functions of windows API and UG/OPEN CAPI, capturing the mouse coordinates in the screen by setting a mouse hook, and projecting the points of theworld coordinate system by calling OpenGL API functions, a point cloud is partitioned into two regions inUGII based on an algorithm of point in-out polygon test.
(3) With the research of the spatial data structure called R-tree which supports dynamic data-managementand the selection of its variation — R*-tree as the spacial data structure of this project, a searching algorithmof K nearest neighbor points in R*-tree is proposed.
(4) Through researching the algorithms of fitting fixed-sphere, transforming coordinates and dataintegration, the algorithm of registration and integration based on least-square sphere is proposed andintegrated with UGII, which can registrate and integrate multi-view point cloud data rapidly and accurately.
(5) Through researching the algorithm of curvature estimate and the principle of data reduction, the datareduction algorithm based on curvature estimation is proposed and integrated with UGII, which can beapplied to any kind of measured data and reduces the mass and dense points directly and effectively.
(6) Through analyzing several previous algorithms of triangulation for scattered data, and establishing theeffective criterion for candidate points, the search and optimizing criterions for match points and fourmethods of data updating, a universal and fast mesh generation algorithm named helix-wave expandingmethod is proposed, which can generate high-quality triangular mesh quickly.
(7) Four algorithms of mesh postprocessing are realized, including inside and outside boundary extraction,data segment, adaptive mesh refinement and mesh model hollowing, which establish the groundwork forfeature line construction, finite element analysis and rapid prototyping.
引文
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[2] YJD Chen. Smooth surface fitting and finite element mesh generation for irregularly distributed data points. Advances in Design Automation, 1993, 65(2): 7~14
[3] David G. Alciatore, Terry T. Wohlers. Importing and reshaping digitized data for use in rapid prototyping: A system for sculpting polygonal mesh surfaces. Rapid Prototyping Journal, 1996, 2(1): 13~23
[4] 朱玉红.反求工程中的三维测量技术.计量技术,2004,(10):5~7
[5] 熊会元,宗志坚,高群等.数控激光扫描测量系统.机械设计与制造,2004,(5):17~19
[6] S Son, H Park, KH Lee. Automated laser scanning system for reverse engineering and inspection. International Journal of Machine Tools & Manufacture, 2002, 42(8): 889~897
[7] 陈志扬.逆向工程技术——应用及软件.CAD/CAM 与制造业信息化,2003,(7):88~92
[8] 将实物零部件转化为可制造的数字模型的唯一全面的解决方案.http:// www. geomagic.com/zh/ products/studio
[9] ICEM Surf 特征和优点.http://www.ptc.com/china/products/icem/icem_08d.htm
[10] Complete Freeform Modeling and Inspection Technology. http://www.ugs.com/ products/nx/ imageware
[11] 从 数 字 化 数 据 产 生 复 杂 表 面 ——CopyCAD . http://www.delcam.com.cn/zhx/copycad/ cadmain.html
[12] 柯映林等著.反求工程 CAD 建模理论、方法和系统.北京:机械工业出版社,2005
[13] UGS. Unigraphics NX 2 产品特点及常用模块功能介绍.UG 产品介绍,2004
[14] 董正卫,田立中,付宜利.UG/OPEN API 编程基础.北京:清华大学出版社,2002
[15] 马晓丽,孙殿柱.基于 UG 二次开发的菜单制作技术.山东理工大学学报(自然科学版),2004, 18(5):33~37
[16] 何炳蔚,林志航.逆向工程中的数据点云的分割.机械制造,2003,(10):11~14
[17] 福利等著. 计算机图形学导论.北京:机械工业出版社,2004
[18] 李维诗,李江雄,柯映林.平面多边形方向及内外点判断的新方法.计算机辅助设计与图形学学 报,2000,12(6):405~407
[19] Feito F, Torres J C. Inclusion test for general polyhedron. Computer and Graphics, 1997, 21 (1): 23~30
[20] 张宁宁,张树有,谭建荣.映射相关边概念的多边形内外点判别算法.计算机辅助设计与图形 学学报,2004,16(7):935~938
[21] Wu Huayi, Gong Jianya, Li Deren, etal. An algebraic algorithm for point inclusion query. Computer and Graphics, 2000, 24(4): 517~522
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