海量车载激光点云组织与可视化研究

车载移动测量系统是一种高精度、高速度的空间信息采集设备,由于获取的点云数据量大,海量车载激光点云的数据处理、三维建模和可视化面临挑战。考虑到车载激光点云沿采集线路逐行扫描形成的特点,提出了一种分块多层叠加型空间索引结构,对海量车载激光点云数据自动分块并建立LOD瓦片结构,实现海量车载激光点云数据的管理与动态调度。实验结果表明:该方法具有有效性和可行性。     

Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques

Accurate and rapid assessment of the as-built status on any construction site provides the opportunity to understand the current performance of a project easily and quickly. Rapid project assessment further identifies discrepancies between the as-built and as-planned progress, and facilitates decision making on the necessary remedial actions. Currently, manual visual observations and surveying are the most dominant data capturing techniques but they are time-consuming, error-prone, and infrequent, making quick and reliable decision-making difficult. Therefore, research on new approaches that allow automatic recognition of as-built performance and visualization of construction progress is essential. This paper presents and compares two methods for obtaining point cloud models for detection and visualization of as-built status for construction projects: (1) A new method of automated image-based reconstruction and modeling of the as-built project status using unordered daily construction photo collections through analysis of Structure from Motion (SfM); (2) 3D laser scanning and analysis of the as-built dense point cloud models. These approaches provide robust means for recognition of progress, productivity, and quality on a construction site. In this paper, an overview of the newly developed automated image-based reconstruction approach and exclusive features which distinct it from other image-based or conventional photogrammetric techniques is presented. Subsequently the terrestrial laser scanning approach carried out for reconstruction and comparison of as-built scenes is presented. Finally the accuracy and usability of both of these techniques for metric reconstruction, automated production of point cloud models, 3D CAD shape modeling, and as-built visualizations is evaluated and compared on eight different case studies. It is shown that for precise defect detection or alignment tasks, image-based point cloud models may not be as accurate and dense as laser scanners' point cloud models. Nonetheless image-based point cloud models provide an opportunity to extract as-built semantic information (i.e., progress, productivity, quality and safety) through the content of the images, are easy to use, and do not need add burden on the project management teams by requiring expertise for data collection or analysis. Finally image-based reconstruction automatically provides photo alignment with point cloud models and enables image-based renderings which can remarkably impact automated performance monitoring and as-built visualizations.     

Analysis of the influence of range and angle of incidence of terrestrial laser scanning measurements on tunnel inspection

Terrestrial Laser Scanner (TLS) measurements are subject to errors which influence the quality of the 3D models built from the point clouds. In this paper, a methodology to build an error model of the TLS measurements is proposed. Measurement errors are estimated based on two of the factors that mostly affect their magnitude: distance to the object and angle of incidence.The error model is used to analyze, by means of Monte Carlo simulation, the spatial distribution of the errors in a point cloud of a circular tunnel section and also to simulate the effect of the measurement error in tunnel inspection works.The results obtained indicate that although the angle of incidence influences the point cloud quality when the laser is located near the tunnel gable, its effect is counteracted by the point density when a surface is fitted to the point cloud.     

基于三维激光扫描的房屋尺寸质量智能化检测方法

基于三维激光扫描技术,提出了一种智能化、全流程的房屋尺寸质量检测方法,包括点云数据配准、点云数据轻量化、房屋逆向建模及尺寸质量检测。通过点云数据映射全景图、基于YOLO v5神经网络模型的标靶纸目标检测以及基于模板匹配方法的标靶中心估计等步骤,可实现多站点云数据之间的自动配准; 通过可分解图滤波算法进行点云数据重采样,实现数据轻量化并提高运行速度; 针对房屋整体点云数据,提出了集点云数据分割、表面重建、尺寸质量检测于一体的综合算法。结果表明:基于标靶纸的点云配准方法能够自动完成各站点云数据的配准,得到完整房屋点云数据; 点云数据分割技术能够分离不同墙面、楼板底面和顶面的点云数据; 表面重建算法能够生成房屋的实体模型; 尺寸质量检测技术能够自动计算出表面的平整度和垂直度; 提出的房屋尺寸质量检测方法全面、可行,且能够适用不同的户型,研究成果以期替代人工测量完成房屋的平整度与垂直度的检测。     

基于EPS2008的地面三维激光扫描技术在隧道测量中应用研究

基于地面三维激光扫描新技术研究与运用,以科技促进发展为目的,通过对隧道测量内容、隧道地物要素分布特征的研究,结合三维激光扫描技术特点,提出了地面三维激光扫描技术在隧道测量中的作业方法及流程;基于EPS2008二次开发技术研究隧道点云特征数据提取方法,实现了基于隧道底面模型的激光点云特征数据提取。     

基于激光点云直接比较算法的边坡变形监测技术研究

 利用三维地面激光扫描技术进行边坡变形监测亟需解决多期激光点云数据的比较问题。通过对Hausdorff距离算法的改进,提出基于八叉树结构的点云与点云的精细直接比较算法,实现变形区域多个点云数据的自动比较,减少人工干预,大大提高变形区域激光点云处理效率。基于上述理论和八叉树结构的点云分块管理和存储方法,开发三维可视化激光点云数据处理分析软件LPCP。将该软件应用于阎家沟滑坡的变形监测分析中,经过与固定点监测数据、DEM分析成果和典型断面的激光点云数据的对比验证分析,发现采用点云精细比较算法计算得到的变形区域和位移量准确,计算效率较高。该方法可以推广应用于各种变形的精细比较分析,大大拓宽了激光扫描技术在高精度变形监测中的应用范围。     

基于三维激光扫描测量技术的井架变形观测

本文基于三维激光扫描测量技术,应用Trimble GX 200地面三维激光扫描仪对山东某矿井架进行了多次井架点云数据采集。首先设计了扫描方案,对获取的点云数据滤波去噪处理并进行了扫描精度检验,其次用目标板的中心拟合坐标分析了井架的垂直变形,最后通过平面拟合方程分析了井架倾斜变形。结果显示相对于传统测量方法,三维激光扫描仪获取大量点云数据能较好地分析井架整体的变形,为矿山井架安全量测提供一种高效、高精度应用方法。     

三维激光扫描技术与GIS在古建筑保护中的应用

本文通过介绍三维激光扫描技术,给出了基于三维激光扫描仪的外业点云测绘实施方案和数据处理流程。结合实例分析了用户对于三维激光扫描点云数据处理软件和生成三维古建筑模型的需求,通过建立古建筑数据库,设计了基于GIS的古建筑数字保护系统。结果表明,三维激光扫描结合GIS技术用于古建筑数字化保护具有重要意义。     

三维激光扫描技术在文物三维重建中的应用研究

三维激光扫描技术为文物高精度三维重建提供了新的途径,为文物的数字化展示、数字博物馆的建立、文物鉴赏以及文化遗产的保存提供了新的思路。本文通过对三维点云数据处理、三维构网、纹理映射、三维模型构建及三维浏览等关键技术研究,解决了三维激光扫描系统用于高精度文物三维重建中的若干技术难题,并精确重建出文物三维模型。     

BIM结合三维激光扫描在建筑中的应用

研究了BIM与三维激光扫描技术结合在建筑中的两类应用。一类应用是针对缺失图纸的建筑,通过三维激光扫描采集点云数据,导入BIM软件中进行逆向建模。二类应用是针对施工监控,通过定期对施工现场进行三维扫描,将处理后的扫描点云与设计模型进行对比,将施工质量以可视化方式进行呈现,便于检验和控制施工质量。     

Autonomous 3D vision-based bolt loosening assessment using micro aerial vehicles

Earlier identification of bolt loosening is crucial to maintain structural integrity and prevent system-level collapse. In this study, a novel drone-based 3D vision methodology has been proposed for autonomous bolt loosening assessment. First, a low-cost micro aerial vehicle with various types of sensors is designed. Second, a drone-based autonomous image collection method is proposed. Third, a 3D point cloud of the bolted connection is generated using the acquired images. Fourth, 3D point cloud processing methods are proposed to localize and quantify bolt loosening. The proposed method has been implemented on structural beam–column connections. The results show that the proposed drone-based data collection method can effectively acquire images for 3D reconstruction. The 3D point cloud processing methods can reliably localize and quantify bolt loosening at high accuracy. The proposed method provides a more robust and comprehensive evaluation of bolt loosening, compared to existing 2D vision methods, which process 2D images captured at a specific camera view.     

不同扫描参数、光照条件对三维激光扫描精度的影响研究

本文提出将三维激光扫描技术应用于变形监测领域,由点云变形计算原理可发现点云密度会对扫描精度造成影响,而光照条件则决定了三维扫描技术的应用场景.基于Trimble TX-8型三维激光扫描仪,通过模拟扫描对象的不同变形状态,系统研究了扫描等级和光照条件对扫描精度的影响,为三维激光扫描技术在变形监测领域的应用打下基础.     

基于激光影像的物体三维点云获取系统

三维点云获取系统能够快速地获取目标物体的几何信息,生成大量点云,将目标的真实三维形态在计算机中可视化的展现出来。本文提出了一种新的三维点云数据获取的方法,应用在自主开发的基于激光影像的物体三维点云获取系统中,即标定激光面映射目标表面点的一维坐标,利用单像摄影测量后方交会和一维坐标的联合解算,得出目标点三维伪坐标。通过坐标逆向旋转恢复,得到真实的三维坐标数据,据此完整地建立目标物体的三维可视化模型。     

三维激光扫描技术应用于建筑基坑变形监测

基坑工程开挖过程中的监测是工程安全的重要保障,为了提高基坑监测的全面性和技术水平,本文通过工程实例介绍了三维激光扫描技术在房屋建筑基坑变形监测中的理论及应用方法,采用三维激光扫描仪获取点云数据并建立了三维偏差模型,与传统的测斜方法等进行了比对和精度分析,提出了提高精度和稳定性的具体改进措施。     

基于激光扫描的高边坡危岩体识别及锚固方法研究

 利用三维激光测量技术获取高陡边坡的高密度点云坐标数据,建立高边坡表面模型。基于三维激光点云数据提取高陡边坡的岩体结构面的产状和几何信息数据。在此基础上,提出危岩块体的识别方法,即将高陡边坡的危岩体点云数据进行构网,形成为块体单元,然后利用虚拟结构面对块体单元进行分割,形成空间块体模型,并根据危岩体失稳类型对空间块体模型进行分类。基于极限平衡理论和各类危岩的破坏机制以及作用在危岩体上荷载组合,建立危岩体锚固计算方法。将该方法应用于东平白佛山边坡的危岩体调查及治理中,根据白佛山边坡危岩体的主要荷载类型(如自重、裂隙水压力和地震力等)及不同类型的危岩体稳定系数,计算不同类型危岩体的最小锚杆数。研究结果表明：(1) 三维激光扫描技术可以远距离、快速获取高陡边坡的空间坐标数据,进而获取岩体结构面的空间信息和产状;(2) 基于危岩体空间坐标数据、结构面空间信息和不同荷载组合,可进行危岩体分类和锚固计算,得到危岩锚固所需的锚杆或锚索数,为危岩锚固治理设计提供依据。工程实例表明,该方法具有较强的适用性和可靠性,有助于高陡边坡危岩体加固方案的设计和优化。     

Structure‐aware 3D reconstruction for cable‐stayed bridges: A learning‐based method

A powerful deep learning‐based three‐dimensional (3D) reconstruction method for reconstructing structure‐aware semantic 3D models of cable‐stayed bridges is proposed herein. Typically, conventional bridge semantic 3D model reconstruction methods are not robust when low‐quality point clouds are used. Furthermore, they are suited particularly for their respective fields and less generalized for cable‐stayed bridges. Hence, a structure‐aware learning‐based cable‐stayed bridge 3D reconstruction framework is proposed. The encoder part of the network uses both multiview images and a photogrammetric point cloud as input, whereas the decoder part uses a recursive binary tree network to model a high‐level structural relation graph and low‐level 3D geometric shapes. Two actual cable‐stayed bridges are employed as examples to evaluate the proposed method. Test results demonstrate that the proposed method successfully reconstructs the bridge model with structural components and their relations. Quantitative results indicate that the predicted models achieved an average F₁ score of 99.01%, a Chamfer distance of 0.0259, and a mesh‐to‐cloud distance of 1.78 m. The achieved result is similar to that obtained using the manual reconstruction approach in terms of component‐wise accuracy, and it is considerably better than that obtained using the manual approach in terms of spatial accuracy. In addition, the proposed recursive binary tree network is robust to noise and partial scans. The potential applications of the obtained 3D bridge models are discussed.     

含油污泥堆肥式处理剂的研究

云冈石窟是一座规模宏大、结构复杂,主要以高浮雕为主的石窟寺,普通的测量方法很难实现云冈石窟的数字化保护。以云冈石窟13窟为例,采用三维激光扫描的方法先获取海量的点云数据,然后利用Cyclone完成点云的拼接,再使用Geomagic生成三维模型和3ds Max实现模型的纹理映射。实践结果表明利用三维激光扫描技术可以高精度、高效率的实现高浮雕石窟寺的数字化。     

三维激光扫描仪点云数据在AutoCAD中的处理

详细介绍了Cyra三维激光扫描系统获取的点云数据在AutoCAD中的处理过程,重点介绍了坐标纠正和进行三维建模的方法与技巧,总结了AutoCAD在三维建模方面的优点,并针对一些处理中的问题提出了一些解决的办法。     

正方形边界悬垂织物自由形态的逆向实现

以正方形边界悬垂织物模型的逆向实验为例,研究自由形态的逆向实现技术,将正方形边界悬垂织物模型经三维扫描,得到表征自由形态特征的点云数据,基于逆向软件处理点云数据,得到重构曲面并生成初始网格,引进条带化旋转展开技术,进一步综合运用三维造型软件与三维打印技术,设计自由形态空间网格结构并可将其快速打印成型,验证了逆向实现技术的可行性。     

Proactive 2D model-based scan planning for existing buildings

Creating a building information model (BIM) is known to be valuable during the life-cycle of a building. In most cases, a BIM of an existing building either does not exist or is out of date. For existing buildings, an as-is BIM is needed to leverage the technology towards building life-cycle objectives. To create an as-is BIM, field surveying is a necessary task in collecting current building related information. Terrestrial laser scanners have been widely accepted as field surveying instruments due to their high level of accuracy. However, laser scanning is a time-consuming and labor-intensive process. Site revisiting and reworking of the scanning process is generally unavoidable because of inappropriate data collection processes. In this context, creating a scan plan before going to a job-site can improve the data collection process. In this study, the authors have proposed a 2D proactive scan-planning framework that includes three modules: an information-gathering module, a preparation module, and a searching module. In addition, three search algorithms — a greedy best-first search algorithm, a greedy search algorithm with a backtracking process, and a simulated annealing algorithm — were compared based on 64 actual building site drawings to identify strength and limitations. The experimental results demonstrate that the greedy search algorithm with a backtracking process could be used to compute an initial scan plan and the simulated annealing algorithm could be used to further refine the initial scan plan. This paper will also introduce the results of a case study that deployed the proposed scan-planning framework. In the case study, the resulting 3D-point cloud that was generated based on the proposed framework was compared with the 3D point cloud created with data collected through a planned scanning process performed by a scan technician.