基于激光扫描点云的数据处理技术研究

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用包含了高斯核函数曲线的曲率表达式建立相关数学模型,选用了合适的离散尺度因子。根据离散曲率曲线的局部极值点,确定出截面线特征点集,并进行特征点的融合。所提出的算法用于准确地获取激光扫描点云的原始设计意图,能最大限度地与原有形状特征元保持一致。顺利地完成逆向建模过程的关键一步。
山东大学博十学位论文 除、滤波和优化修正量光顺处理之后的海量点云数据。该压缩算法简单直观, 能够根据公差值4和角度最大允差值的大小来压缩数据,这一点能最大限 度地满足机械产品外形和精度要求。能够最大限度地保留原有点云数据的外 形,提高压缩后数据点的精度,对海量点云数据的压缩具有实际应用价值。 针对所采集的激光扫描点云密集和数据量大的特点,重点研究了截面线 点云数据的光顺处理,这方面比较著名的文献包括,EckM, Jaspert r和GH Liu,Y.S. Wang and Y F. Zhang所提出的光顺算法,可是,GHLj和Y.S.Wang 等人所提出的光顺算法,其修正量是递进的,利用寻优函数的约束来确定修 正量,从而使坏点得到光顺,其修正量的阈值没有限制;修正方向的指向是 按照能量函数方程符号的变化作出决定,其编程实现相对复杂。由此,本文 提出了一种优化修正量光顺算法,在分块进行粗、精光顺处理采样数据过程 中,分别由曲率及其一阶差分符号的变化来辨识坏点。坏点的修正方向直接 按照能量函数方程确定出由型值点指向三角形形心的正或负的G向;修正量 由赋初值开始,然后按照能量函数方程,递进搜索,满足能量代数式最小值 后搜索停止。本文所提出的优化修正量光顺算法,主要用于光顺激光扫描散 乱点云数据,该算法能够满足曲线曲面重构的光顺性要求,可以有效保留曲 线的原有几何外形。最后通过在二维散乱点云上的实例仿真,验证了所提算 法的适用性和有效性 〔3)提出了用离散曲率算法进行截面线特征提取。 特征提取是逆向工程的重要步骤,其中截面线特征点的弱化是需要解决 的关键问题。本文重点研究了二维截面线特征点的提取。检索到有关特征点 直接提取的文献有,自适应k-曲率(AKC)函数算法,在断点提取中,AKC函 数是用于提取拐角和光滑连接之间的特征点;映射高度函数(PHF)算法,PHF 函数用于从圆弧中区分出直线段的特征点提取;由Li和Ma提出的相对转 角绘图(RSTM)算法,用于辨识轮廓线的特征点提取问题。AKC函数算法和 PHF算法只能提取某种特征点,其广泛应用受到一定限制。 在研究了特征点直接提取上述文献相关算法的基础上,提出用离散曲率 法提取特征点。所提出算法的主要内容包括:用包含了高斯核函数曲线的曲 率表达式建立相关数学模型,选用了合适的离散尺度因子。根据离散曲率曲 线的局部极值点,确定出截面线特征点集,并进行特征点的融合。所提出的 摘要 算法用于准确地获取激光扫描点云的原始设计意图,能最大限度地与原有形 状特征元保持一致。顺利地完成逆向建模过程的关键一步。在实例应用中, 把RSTM算法和所提出的离散曲率算法在实例应用上做了输出比较,结果 是,本文提出的离散曲率算法特征点提取问题,能够提取弱化的特征点,不 容易出现特征点的漏检问题,是一种适用和有效的算法。 关键词激光扫描;点云数据;切片;噪声点去除;优化修正量光顺; 点云压缩;离散曲率法;特征提取 Abstract Abstract With the development of computer and mechanical manufacturing technology, reverse engineering has been widely used in product re-innovation and design. As a research hot topic of geometrical components and an important geometric modeling technique in reverse engineering, data processing technology based on laser scanning point cloud which is regarded scattered point cloud data as the the basic element during the process of data pre-processing and modeling, and which is so important that it is full of development at home and abroad at present time. The data processing technology, regarded the obtained point cloud data as processing objects and without building a triangular mesh, now shows its unique advantages and is becoming a hot research spot, during the process of dealing with very large scale point cloud, point cloud data preprocessing, feature extraction and mode reconstruction. In this paper, some key issues in the field of reverse engineering have been developed deeply, which is helped by the National Natural Science Foundation of Shandong Province Complicated Surface Reconstruction Technology Research Based on Multi-scale Features" (Item Number: Y2006F12) 1)In order to meet the precision of following product development and reconstruction in reverse-engineering, mathematical description and classification about noise have been completely finished and a set of data pre-processing process has been set up, which can minimize or effectively eliminate the noise According to the characteristics of laser scanning point cloud data, some mathematical description and generated mechanism of noise points are descriped. Based on the established mathematical model, the noise points are classified into two categories, one is that caused by the system measurement error a(, yi, zi) and the system random error B(,yi, z, the other is that Supported by the National Natural Science Foundation of Shandong Province(Y2006F12 山东大学博十学位论文 caused by the random component g(x, yi, zi), the removal of which is carried up according to their characteristics relied on some feasible de-noised methods. So, a set of de-noised process of data pre-processing is developed, including the removal of obviously noise points, smoothing filter process of noise points, and smoothing process of point cloud data, etc.. The run results show that the de-noised pre-processing process can minimize noise points, and can meet the precision of following product development and reconstruction in reverse-engineering based on the sliced point cloud data (from three-dimensional discrete point cloud data of the model to the obtained point cloud data of two-dimensional cross-section contour), which caused by system measurement error, system random error and system random component (2)The he preprocessing algorithms about massive laser scanning point cloud data have been studied, and an optimized amount of smoothing algorithm has been proposed In this paper, an bias parameter algorithm and an allowable difference of angle is presented to compress point cloud data, under the condition of intensive and massive laser scanning point cloud data which is not easy to store, and data accuracy assured after data compression, which is used to process laser scanning point cloud data through the big noise points removal, filtering and optimal amount smoothing process. The above mentioned compression algorithm is simple and intuitive, which can compress the data based on the size af the tolerance values about bias parameter and bias angle, and can meet the required appearance and precision of mechanical products greatly. The algorithm can preserve the original shape of point cloud data, and can improve the accuracy of the compressed data points, which has practical application value on the compression of massive point cloud data As the collected laser scanning point cloud data is intensive and large, some smoothing process algorithm about laser scanning point data of a section curve have been mainly researched. The well-known literatures in this field, Eck M, Jaspert R, and G.H. Liu, Y.S. Wang and Y F Zhang, in which an smoothing Abstract algorithm is proposed. However, the smoothing algorithms are proposed by G.H. Liu and Y.S. Wang etc, the revised amount is progressive, and the constrained optimizing function is used to determine the amendment amount, which has no limit to the threshold value. And the revised direction to point is determined in accordance with changes of energy function equation symbols, in which the its program is relatively complex. Thus, an optimized amount of smoothing algorithm is presented in this paper, which identified bad points in accordance with the sign change of their curvatures and corresponding first-order differences during the process of coarse smoothing and fine smoothing. The corrected direction of bad points is pointed to the positive or negative G of the triangle centroid from the sampled data in accordance with the energy function equation. The revised amount has been an incremental search, beginning with an initial value and then following the energy function equation, until the minimum value of energy algebraic expression is meet. The proposed optimized amount smoothing algorithm in this paper, mainly used for smoothing scattered laser scanning point cloud data, can meet the smoothness requirements of curve and surface reconstruction. The proposed algorithm is particularly effective in terms of shape preservation. Case studies are presented that illustrate the efficacy of the proposed algorithm (3)A discrete curvature algorithm is proposed to extract feature points of a sectional curve Feature extraction is an important process in reverse engineering, in which weak feature points of a sectional curve is the key issues to be dealed with The feature points extraction of two-dimensional cross-sectional curve is focused on in this paper. The retrieved literatures about feature points extracted directly include the adaptive k-curvature (Akc) function algorithm, which is used to extract the feature points between corner and smooth connection, the mapping height function (PHF)algorithm, which is used to distinguish feature points from arc and line segments, and the relative angle mapping (rStm)algorithm proposed by Liu and ma, which is used to identify the feature points of contours 山东大学博十学位论文 The AkC function algorithm and phf algorithm can only extract some certain feature points which has certain restrictions used in the wide field Based on directly extracting feature points of the above-mentioned documents, the discrete curvature method is proposed to extract feature points The main contents of the proposed algorithm include, the curvature expression comprised of Gaussian kernel function curve is used to establish the relevant mathematical models, and a suitable discrete scale factor is chosen. According to the local extreme points of discrete curve, a set of feature points is determined, and the fuse of feature points is carried out subsequently. The proposed algorithm is used to accurately obtain the original design intent of the laser scanning point cloud, which can greatly keep with the original shape feature cell consistently. Then a key step in reverse modeling process is successfully completed. During the course of example application, an output comparison between the Rstm algorithm and the proposed discrete curvature algorithm has been carried out, which the the result is that the proposed method in this paper can extract the weak feature points and cannot prone to undetect feature points. Then the output results show the proposed algorithm is practical and effective Keywords: Laser scanning; Point cloud data; Slice; noise points removal;An optimized amount smoothing algorithm; Point cloud compression; Discrete curvature algorithm; Feature extraction 原创性声明 本人郑重声明:所呈交的学位论文,是本人在导师的指导下, 独立进行研究所取得的成果。除文中已经注明引用的内容外,本 论文不包含任何其他个人或者集体已经发表或撰写过的科研成 果。对本文的研究做出重要贡献的个人和集体,均已在文中以明 确方式标明。本人完全意识到本声明的法律责任由本人承担。 论文作者签名: 孟 日期:20019日20日 关于学位论文使用授权的声明 本人完全了解山东大学有关保留、使用学位论文的规定,同 意学校保留或向国家有关部门或机构送交论文的复印件和电子 版,允许论文被查阅和借阅;本人授权山东大学可以将本学位论 文的全部或部分内容编入有关数据库进行检索,可以采用影印、 缩印或其他复制手段保存论文和汇编本学位论文 (保密论文在解密后应遵守此规定) 论文作者签名五型导师签名:日期2辉:12日 第1章绪论 第1章绪论 .1引言 产品的快速开发和创新设计是决定企业是否具有竞争力的关键。在新产 品的创新开发过程中,出现了许多先进设计和制造技术,如逆向工程,三维 CAD/CAE/CAM、并行工程(CE)、虚拟制造(VM)、快速成型(RP)等。逆向工 程( Reverse engineering,RE)作为消化吸收已有产品的成果和先进技术,并进 行创新开发的手段,其理论研究和应用开发越来越受到工程技术人员和科研 工作者的重视,其直接的目的是,希望以较低的成本和更高的效率对原型产 品进行开发、创新和设计,从而为国民经济和国家现代化建设做出应有的贡 献 [-4] 1.1.1向工程基本概念 逆向工程( Reverse Engineering,RE),也称反求工程、反向工程等。逆 向工程起源于精密测量和质量检验,它是设计下游向设计上游反馈信息的回 路 传统的产品实现通常是从概念设计到图样,再制造出产品,我们称之为 正向工程(或顺向工程),而产品的逆向工程是根据零件(或原型)生成图样, 再制造产品。它是一种以先进产品设备的实物、样件、软件(包括图样、程 序、技术文件等)或影像(图像、照片等作为研究对象,应用现代设计方法学、 生产工程学、材料学和有关专业知识进行系统分析和研究、探索掌握其关键 技术,进而开发出同类的更为先进的产品的技术,是针对消化吸收先进技术 采取的一系列分析方法和应用技术的结合。广义的逆向工程包括形状(几何) 逆向、工艺逆向和材料逆向等诸多方面,是一个复杂的系统工程。本文为形 状逆向⑤。 目前,大多数有关“逆向工程”技术的研究和应用都集中在几何形状, 即重建产品实物的CAD模型和最终产品的制造方面,称为“实物逆向工程”。 这是因为一方面,作为研究对象,产品实物是面向消费市场最广、最多的一 类设计结果,也是最容易获得的研究对象;另一方面,在产品开发和制造过 程中,虽已广泛使用了计算机几何造型技术,但是仍有许多产品,由于种种

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