反求工程中三角网格拓扑生成的算法研究

散乱点的三角网格剖分是反求工程中的第一个重要环节，在对三角剖分基本方法深入分析的基础上提出了动态圆的概念，使得搜索新三角形的范围大大降低，从而加快速度，并在搜索过程中实现Delauuay三角形优化，另外，通过动态更新搜索边控制三角形生成进度，将新三角形和已有三角形的相交判定转化为和搜索边的相交判定。     

一种新的空间离散点集的直接三角剖分方法

针对映射法无法保证在平面中所谓“优”的三角剖分所对应的空间形状也满足要求的缺点,文中提出了一种对空间离散点集进行直接三角剖分的新方法——在形成了初始三角形后,利用生长法,循环扩展三角形各边,直至所有三角形扩展完毕。在算法实现上,提出了利用三角形法向量夹角、阈值距离以及最小内角几个参数,对三角形的生长进行约束,从而使最优点的搜索范围大大降低,提高了三角形扩展的准确性,保证了三角网格的质量。实验证明,该方法适应性广并具有准确、高效的特点。     

一种空间曲面上散乱数据的快速三角剖分新算法

在现有三角剖分方法研究的基础上,提出了一种空间曲面上点云数据的快速三角剖分新算法。以区域生长法为主导,通过表面法向量向外原则提出了一种种子三角形选取与构造的新方法,改进生长算法,采用逆时针方式搜寻最优扩展点来生成三角形网格。该算法的总体时间复杂度为O（KN）,能够快速高质量的生成三角网格模型。     

散乱数据点的快速三角剖分算法

提出了一种改进的波前扩展算法,该算法给出的候选点判断准则,可对数据点的K近邻进行快速过滤,并有效避免了单元自相交;建立的匹配点查找和优化准则,可生成局部优化的三角形网格单元;依据四种不同的查询结果,制定了相应的波前环更新和数据点标记方法。将波前扩展算法应用于具有复杂特征的散乱数据点的三角剖分中,结果表明,该算法可快速生成高质量的三角网格模型。     

反求工程中基于边界扩展的三角网格构造

针对非接触式方式测量的大规模散乱点云数据建模，提出一种三角剖分算法，该算法适用于多张自由曲面片构成的曲面物体，尤其适用于含内孔的曲面对象。算法过程包括两个阶段：第一阶段，采用一种空间栅格装点法来进行初始点云数据精简，精简比率通过栅格小正方体单元尺寸控制；第二阶段，构造种子三角形，通过连接已剖分网格区域的边界边与最优扩展点采形成三角网格，从而向外延展，也可以时一个带有内孔的复杂自由曲面直接进行三角剖分，无需人工分区。实验结果表明该算法可以快速、有效地从三维数据点云建立几何模型。     

散乱数据点的快速三角剖分算法

提出了一种改进的波前扩展算法,该算法给出的候选点判断准则,可对数据点的K近邻进行快速过滤,并有效避免了单元自相交;建立的匹配点查找和优化准则,可生成局部优化的三角形网格单元;依据四种不同的查询结果,制定了相应的波前环更新和数据点标记方法.将波前扩展算法应用于具有复杂特征的散乱数据点的三角剖分中,结果表明,该算法可快速生成高质量的三角网格模型.     

散乱模型的四边形网格剖分方法

针对基于CAD几何信息的网格剖分方法无法避免繁琐模型修补,导致网格剖分效率低下的现状,提出一种基于散乱模型的全四边形网格剖分方法.使用散乱点或者STL格式文件作为网格剖分的输入模型,使用改进的基于散乱模型进行网格剖分的铺路算法,在很大程度上减少甚至避免了模型修补问题.提出以散乱模型作为背景网格,作为控制网格单元尺寸调整的依据:使用网格细分和网格粗化的手段实现网格疏密变化的光滑过渡;自动识别几何模型中的特征并在网格模型中保留.提出了一种高效的铺路面相交搜索方法,综合考虑影响相交处理的多种因素,有效地处理了铺路面相交问题.多个复杂的汽车覆盖件网格剖分的算例结果表明,运用所提出方法完成的网格模型质量很高,算法具有较强的工程实用性.     

一种基于神经元增长结构(GCS)的空间散乱点三角剖分方法

空间散乱数据点的三角剖分是逆向工程的关键技术,本文提出了基于一种动态神经网络———神经元增长结构(GrowingCellStructure)的空间三角剖分新方法。这种方法具有可以直接处理带有噪声的数据,无需对数据进行平滑处理,网格规模可控,算法简单,生成的三角网格形状好等优点。     

基本体素的三角形面单元剖分方法

研究了基本体素的三角形面单元剖分方法。以正三角形单元为基础给出了圆柱体和圆台体的三角形面单元剖分详细方法。以Visual C++6.0为开发工具,对三角形面单元剖分方法进行了仿真实验。剖分数据的实验结果验证了所研究方法的正确性。     

截面扫描型点云数据的三角剖分算法

截面扫描型点云数据三角剖分的难点在于在三角剖分中找到一个合适的数学模型来统一各条扫描线点个数。本文利用NURBS曲线的表达式作为数学模型,提出了基于曲线相容性的三角剖分方法。首先对截面轮廓数据进行排序,用NURBS曲线进行拟合,然后对截面曲线进行相容性操作,在离散的基础上实现了三角剖分算法。     

DELAUNAY-BASED SURFACE RECONSTRUCTION ALGORITHM IN REVERSE ENGINEERING

Triangulation of scattered points is the first important section during reverse engineering. New concepts of dynamic circle and closed point are put forward based on current basic method. These new concepts can narrow the extent which triangulation process should seek through and optimize the triangles during producing them. Updating the searching edges dynamically controls progress of triangulation. Intersection judgment between new triangle and produced triangles is changed into intersection judgment between new triangle and searching edges. Examples illustrate superiorities of this new algorithm     

STL File Generation with Data Reduction by the Delaunay Triangulation Method in Reverse Engineering

Reverse engineering has been widely used for the shape reconstruction of an object without CAD data and typical steps include the scanning of a clay or wood model and the generation of manufacturing data such as an STL file. A new approach to remove point data with Delaunay triangulation is introduced to deal with the size problems of the STL file and the difficulties in the operation of the rapid prototyping (RP) process. The selection of a group of triangles, based on the angle, is used for a robust and reliable implementation of the Delaunay triangulation method. The developed software enables the user to specify the criteria for the selection of the group of triangles by the angle between triangles, the percentage of reduced triangles, and the allowable area. This approach can be used to reduce the measuring data from the laser scanner, thus save the handling time of point data during the modelling process and is useful for verifying and slicing the STL model during the RP process.     

基于断层序列图象的三角域拓扑模型快速剖分算法研究

介绍了一种对三角域拓扑模型进行任意截面快速剖分的算法:在断层序列图象的三维重建过程中,划分并规整三角面片,然后以空间立方体序列的形式进行组织,得到具有清晰毗邻关系和索引结构的表面模型。在以任意角度截面剖分模型时,根据空间立方体的索引关系快速检索被切割到的三角面片,依次进行剖切处理,最终得到三维模型的任意剖面轮廓线。该算法在实际中得到应用,效果良好。     

GENERATE TRIANGUUTED SURFACES FROM MASSIVE UNORGANIZED POINTS

A region-growing method for reconstructing triangulated surfaces from massive unorganized points is presented. To save memory space, a ring data-structure is adopted to build connections between points and triangulated surfaces. The data-structure allows the efficient retrieval of all neighboring vertices and triangles of a given vertice. To narrow the search range of adjacent points and avoid mangle intersection, an influence area is defined for each active-edge. In the region-growing process of triangulated surfaces, a minimum-edge-angle-product algorithm is put forward to select an appropriate point to form a new triangle for an active edge. Results indicate that the presented method has high efficiency and needs less memory space, optimized triangulated surfaces with reliable topological quality can be obtained after triangulation.     

STL文件拓扑关系的建立与新型三角片搜索算法研究

通过对STL文件结构的分析，用改良的无向图数据结构来建立三角形网格之间的毗邻关系网，弥补了STL文件结构固有的缺陷。通过对截平面与三角形之间所有位置关系进行的研究，提出了新的三角形网格搜寻方案，能够顺利搜索到下一个三角形。最后生成的截面轮廓沿Z轴方向看，外轮廓的边界点按其序号大小沿逆时针方向排列，内轮廓的边界点按其序号大小沿顺时针方向排列。     

塑性成形三维数值模拟网格表面轮廓节点处理方法

以DEFORM-3D软件为例，提出基于点对来获取模具型腔轮廓节点的方法，并用c 语言加以实现，得到精确的模具截面边界曲线，为研究模具和工件变形提供方便高效的手段。     

一种受约束的散乱点三角划分方法

提出了一种基于区域分割的方法来解决受任意边界、孔域、特征线约束的二维散乱点的三角划分问题。该方法分两个步骤 ,第一步实现散乱点的初始三角形连接 ,第二步实现三角形网格优化。在初始三角形连接中 ,每连接一个三角形 ,将待划分区域分为两至三个较小的区域 ,然后分别对每个区域内的散乱点进行三角划分 ,这样一直迭代下去 ,直至没有新区域出现为止。本方法不仅能解决非凸边界、孔域、特征线嵌入等三角划分中的难点 ,而且其计算量也少     

Triangular mesh generation employing a boundary expansion technique

This paper presents a triangulation method for modelling very large sets of cloud data. The three-dimensional (3D) data sets are produced by a machine vision system and/or coordinate measuring machine (CMM). The algorithm is suitable for processing the data collected from objects composed of free form surface patches especially with interior holes. This is accomplished from the 3D data sets in two steps. Firstly, the original cloud data is reduced into a simplified data set employing a data reduction technique (voxel binning method), in which the error between the cloud data and the meshed surface is used to control the data reduction. Secondly, the triangulation process starts with a randomly selected seed triangle. The triangular mesh extends outward by continuously linking suitable external points to it along the boundary edges of the meshed area. A complex free form surface with interior holes can be triangulated in one computing session without manually dividing it into several simple patches. The error-based data reduction parameters are extracted from the cloud data set, by a series of local surface patches, and the required spatial error between the final triangulation and the cloud data. Experimental results are given to illustrate the efficacy of the technique for rapidly constructing a geometric model from 3D digitised cloud data.     

RESEARCH ON ADAPTIVE DATA COMPRESSION METHOD FOR TRIANGULATED SURFACES

NC code or STL file can be generated directly from measuring data in a fas re-verse-engineering mode. Compressing the massive data from laser scanner is the key of the new mode.An adaptive compression method based on triangulated-surfaces model is put forwar. Normal-vectoranges between triangles are computed to find prime vertices for removal. Ring data structure isadopted to save massive data effectively. It allows the efficient retrieval of all neighboring vertices andtriangles of a given vertices. To avoid long and thin triangles, a new re-triangulation approach based onnormalized minimum-vertex-distance is proposed, in which the vertex distance and interior angle oftriangle are considered. Results indicate that the compression method has high efficiency and can getreliable precision. The method can be applied in fast reverse engineering to acquire an opimal subsetof the original massive data.