基于散乱点云模型的自适应分层方法研究

针对在分层过程中,如何调节分层效率与成型精度之间矛盾的问题,通过对现有分层算法,分层过程中初始分层厚度确定、数据精简及轮廓线拟合等方法的研究,提出了一种基于点云距离变化的自适应分层算法。基于散乱点云模型,通过计算每层切片中各线段与最近点的距离,筛选出了距离的最大值;计算了相邻两层之间最大距离的变化率,然后与设定的阈值进行了比较,自动地调整了分层厚度;经过对斗齿点云模型的分层实验,验证了算法的有效性。实验结果表明:该算法能够在一定程度上平衡分层效率和成型精度之间的关系,并且适应于高精度、型面较复杂模型的分层。     

采用截面特征点云的NURBS自由曲面构建

结合NURBS曲面的构建理论,以工程软件UG为平台,探讨了基于截面特征点云的NURBS自由曲面构建的工程实现方法.实现了由截面特征点云进行NURBS曲线拟合,再由拟合曲线进行自由曲面的构建过程,并从曲面的表面状态与误差两个方面对构建的自由曲面进行评估.实践表明:采用该方法构建的自由曲面能保证NURBS曲面拟合质量,且精度高,能有效地反映实物原型.     

基于自由曲面点云的快速原型制作技术研究

针对不附加任何拓扑和几何信息的云状数据三维重建问题,提出了对点云直接进行分层处理快速制作原型的新方法。在对点集进行空间结构划分的基础上,采用最小距离关联点对方法提取层面轮廓线数据,并对其加以匀化和精整从而直接生成快速成形机的层片接口文件,避免了常规方法存在的耗时和需要很高的造型技巧等不足,而且片面的错误校验与修补等繁琐工作也将不再进行,提高了快速成形前处理的效率,非常适合分层实体制造(LOM)等成形工艺。     

基于B样条曲面的点云孔洞拟合填充

为了后续曲面重构的需要,针对有孔洞的点云数据,提出了一种孔洞拟合填充的自适应方法.由于孔洞与其周围离散点有一定的连续性,该算法首先从孔洞周围已有的点云数据中选取离散点,用新的参数化方法对得到的离散点参数化后,用最小二乘法进行自适应曲面拟合,对得到的拟合曲面通过迭代法逐步逼近优化,考虑曲率变化的影响在曲面上取点,实现了孔洞光滑填充.实例表明,改进的参数化方法使算法的复杂度减低,进一步迭代优化提高了曲面拟合精度,在面上取点时考虑了曲率变化,因此该方法可以应用于具有复杂曲面形状的点云中的孔洞填充.     

基于B样条曲面的点云孔洞拟合填充

为了后续曲面重构的需要,针对有孔洞的点云数据,提出了一种孔洞拟合填充的自适应方法。由于孔洞与其周围离散点有一定的连续性,该算法首先从孔洞周围已有的点云数据中选取离散点,用新的参数化方法对得到的离散点参数化后,用最小二乘法进行自适应曲面拟合,对得到的拟合曲面通过迭代法逐步逼近优化,考虑曲率变化的影响在曲面上取点,实现了孔洞光滑填充。实例表明,改进的参数化方法使算法的复杂度减低,进一步迭代优化提高了曲面拟合精度,在面上取点时考虑了曲率变化,因此该方法可以应用于具有复杂曲面形状的点云中的孔洞填充。     

基于自适应测量和实时重构的自由曲面特征产品的逆向研究

为提高自由曲面测量速度和重构精度,基于三坐标测量机CMM,提出自适应测量的曲面重构方法。测量过程中,通过不断拟合样件上已测点,预算待测点及其测量矢量,指导CMM自动采集曲面上数据。由点云拟合自由曲面模型后,检验拟合模型上点与样件上相应点的误差;若误差偏大,则在测量点云中加入检测点后重新拟合曲面,进一步检测重拟合实体模型直至满足精度要求,得到精准数据点和精致的自由曲面模型。辅以计算机图形可视化实例验证本法,测量精度及其重构精度可达μ级,具有自由曲面特征的零部件整个逆向周期呈数量级下降,算法鲁棒性强。     

基于散乱数据截面线的曲面重构算法研究

提出了一个新的散乱数据的曲面重建算法，该算法采用一组平行平面去剖切点云，除恰好位于该截面上的数据点之外，如果一数据点与某一截面的距离小于给定的距离域值，则将其投影到该截面上，把上述点通称为用距离域值来确定截取点：将每一张截面上的截取点用最小二乘法拟合成B样条曲线，然后对生成的一组B样条曲线进行处理，即统一节点矢量、重新参数化和起点相对应，重新拟合一组闭合B样条曲线，再对其运用蒙面操作，从而构造一张曲面。     

基于支持向量回归机的点云曲面重构方法

提出了一种基于支持向量回归的点云曲面重构方法,并以径向基函数为核函数重建复杂线性函数曲面模型,实验表明该方法能直接重建散乱点数据,具有误差小,速度快等优点.     

基于Level Set方法的点云建模技术研究

描述一种利用偏微分方程(PDE)和变分法进行点采样几何模型重建算法.把符号距离函数与任意函数的度量函数作为内部能量,根据能量约束最小化条件,通过Level Set方法求解曲面的梯度流.使初始曲面随时间产生演化变形,直至逼近目标模型,完全消除重新初始化过程.实验表明,通过Level set方法能够把初始曲面快速自动演化变形到目标模型,对任意拓扑结构和带噪声的点云具有很强的适应能力.     

基于光线测试的点云数据与CAD模型归属处理研究

针对非接触测量方法进行复杂型面零件数字化检测中,点云数据量大及点云与计算机辅助设计模型配准和偏差计算中存在着如何有效处理点云与测量面的归属问题,提出了采用光线测试模型确定计算机辅助设计模型的可见面.以待测计算机辅助设计模型面的采样型值点作为光源,其外法矢作为光源方向与计算机辅助设计模型进行相交测试,确定出测量可见面,然后进行点云与可见面的归属处理.试验结果证明了该方法的有效性.     

基于点云处理技术的喷涂机器人喷枪轨迹生成研究

提出了以点云数据作为喷涂机器人轨迹生成的数据格式,采用点云处理技术,通过对点云的预处理、区域分割,点云切片、采样点求取法矢量及沿法矢量方向偏移等方法实现了喷涂机器人轨迹的生成。将点云技术运用到喷涂机器人轨迹规划,通过点云区域分割细化了点云特征,降低了喷涂工艺的复杂性,同时很好的控制喷枪的位置,提高了喷涂的质量和效率。     

曲面重构中散乱点云数据曲率估算算法的研究

获取测量点云数据的几何特征信息是曲面重构的基础,估算数据点方向矢量和曲率是点云数据处理中必须面对的问题。这里针对散乱测量数据点云,以局部数据点协方差矩的最小特征向量作为数据点的方向矢量,并根据实际测量情况,对基于二次曲面拟合的数据点曲率估算算法进行了改进。对实际测量点云数据,能够较准确地估算出点云方向矢量和曲率,并能形象显示出数据点云的曲率分布。     

Adaptive direct slicing with non-uniform cusp heights for rapid prototyping

Adaptive slicing varies layer thickness by taking the geometry change of the CAD model in the build direction into account to improve surface finish. Direct slicing generates exact slice contours from the original CAD model and avoids an intermediate representation, known as an STL file. At present, most direct slicing approaches are restricted to some CSG solids or some CAD systems. In this paper, an approach toward adaptive direct slicing with non-uniform cusp heights independent of CAD systems for rapid prototyping is presented. First the geometry model is imported into the adaptive direct slicing system from CAD systems using the standard STEP format. Using OpenGL graphics libraries, the solid model is then displayed and the user is prompted to specify the allowable cusp height for each highlighted surface. Lastly, the CAD model is sliced adaptively with different cusp heights (tolerance requirements) for different surfaces. With non-uniform cusp heights, adaptive slicing has a higher efficiency. Implementation details and results are also presented.     

基于Surfacer的点云数据的预处理研究

“点云”的预处理研究,包括平滑和拓扑关系的建立。利用反求软件——Surfacer,对“点云”进行了平滑,然后直接从空间入手,从一般性的角度来说明了点云数据的三角剖分的算法,建立数据之间的拓扑关系。文中最后指出下一步的工作。     

AutoCAD环境下直接适应性切片方法及实现

数据分层处理是快速成型技术的核心.适应性分层可以有效解决快速成型中成形精度和速度之间的矛盾.利用AutoCAD二次开发技术,通过比较相邻层片截面的面积确定切片厚度,提出了一种基于CAD模型的直接适应性切片方法,并对该方法进行了实现,同时与定层厚切片方法进行了比较,最后给出了分层实例并对结果进行了分析.     

Adaptive slicing of functionally graded material objects for rapid prototyping

Slicing is a fundamental process planning task and an important procedure in rapid prototyping. However, most research currently focuses on the slicing of homogeneous objects and few approaches for slicing of heterogeneous objects have been reported in the literature. In this article, we present an approach for adaptive slicing of functionally graded material objects. Unlike homogeneous objects, functionally graded material objects contain both geometry and material information. The layer thickness is computed by considering not only geometry but also material variation along the build direction. The continuous material distribution in each layer is discretised into step-wise gradings by subdividing the slice into sub-regions, which can be regarded as homogeneous material regions. An algorithm that summarised the slicing procedure is described and an example is also presented.     

Adaptive direct slicing of a commercial CAD model for use in rapid prototyping

Slicing a 3D graphic model into layers of 2D contour plots is an essential step for all rapid prototyping (RP) machines. Various methods are available, such as stereo lithography (STL) file slicing, direct slicing and adaptive direct slicing. Amongst these, adaptive direct slicing is the most advanced for its capability of adapting the slicing thickness according to the curvature of any contour. In this study, an adaptive direct slicing method complete with the algorithm for calculating the thickness of each layer is proposed. As an illustration of the method, the algorithm was programmed within the commercial CAD software package, PowerSHAPE. The method was shown to be fast and accurate in comparison with STL file slicing and direct slicing, which both used a constant layer thickness. An erratum to this article can be found at     

Improved intermediate point curve model for integrating reverse engineering and rapid prototyping

Direct integration of reverse engineering and rapid prototyping removes two intermediate steps of surface fitting from point cloud data and STL file generation from CAD models. Therefore errors introduced due to surface fitting and triangulations are eliminated and also the process of STL data validation and repair is avoided. Intermediate point based curve model (IPCM) method is one of the promising approaches for direct integration of reverse engineering and rapid prototyping however this approach has the limitation that it cannot handle objects, which result in multiple contoured slices. Moreover, IPCM based method is implemented with layers of constant thickness slices, and adaptive slicing with this method is not attempted. The present work is an attempt towards improving the capabilities of IPCM based method by overcoming the above-mentioned two limitations. The new system developed here has been tested on many parts, which demonstrates the capability of the proposed system. An erratum to this article can be found at     

A methodology for smoothing of point cloud data based on anisotropic heat conduction theory

It is necessary to smooth point cloud data in reverse engineering or the inspection of free-form surfaces because noisy points will have a negative influence on the post-processing of this data. The big problem in smoothing point cloud data is how to solve the dilemma between removing noisy points and keeping feature boundary information, whilst controlling the diffusiveness of noisy points. In this paper, the theory of anisotropic heat conduction is adopted to establish a mathematical model of point cloud data smoothing. The point cloud data can be considered as a temperature field with an adiabatic boundary. So the heat is only conducted inside the temperature filed and has no effect on the outer side. For point cloud data, it means that the smoothing is only on the local area, which makes a good balance between deleting noisy points and keeping feature boundary information. The method has been implemented by using two cases for practical application, and the result proves its efficiency.     

Complete 3D surface reconstruction from unstructured point cloud

In this study, a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out. Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.