基于激光扫描技术的水库大坝三维变形动态监测方法研究

发布时间：2019-01-26 07:40

【摘要】：大坝变形监测是大坝安全监测的重要监测项目,在水库防洪安全中发挥着重要的作用。目前大坝变形监测的手段和方法存在一些不足,随着三维激光扫描技术的飞速发展,给大坝变形监测提供了新的技术支持。三维激光扫描能够获取丰富、完整的大坝三维点云数据、影像数据及反射强度等信息,并且具备了高效、高精度、主动性的特点,使得它能够应用于大坝变形监测。本文以土石坝三维变形分析为主,从土石坝点云数据采集、处理到大坝变形分析,尝试解决三维激光扫描技术应用于大坝变形监测的关键技术问题。三维激光扫描技术打破了传统单点一维大坝变形监测的局限,从三维、整体上进行大坝变形监测分析,有助于提高变形监测分析的精度与可靠性,为大坝安全评估提供更加可靠的科学依据。全文从利用点云数据进行大坝变形监测技术与方法入手,围绕着提高土石坝变形监测精度与效率展开。为了提高多站海量大坝点云数据拼接精度与效率,研究了基于球体标靶的多站海量大坝点云数据自动拼接技术,解决了海量点云数据组织与管理的索引方法与球体标靶的拟合算法,通过实验证明了该方法具有较高拼接效率和精度。大坝变形分析是本文的重点和难点,本文提出了基于散乱点云剖面数据的变形分析方法与基于大坝精准三维模型的变形分析方法。重点解决了散乱大坝点云数据剖面线的拟合以及变形分析算法,通过序列点云的剖面数据对大坝变形进行分析。为了构建大坝精准三维模型,改进了基于自适应曲面体元的大坝三维表面精准模型构建,有效解决了构网效率低下、表面空洞、法向不一致及面片重叠等问题,为大坝精准对比分析打下良好的基础。在分析和对比基于DEM、基于邻近点和基于C2M(cloud to mesh)变形分析方法的基础上,充分考虑散乱点云数据源的不确定性,提出了基于散乱点云粗糙度置信区间的多尺度大坝变形分析方法,并解决该方法中核心点计算、粗糙度计算以及不同尺度下空间置信区间的参数设定问题,通过实验分析验证该方法的可行性与有效性,并与基于大坝精准三维模型的变形分析方法进行了对比,验证了该方法的精度。
[Abstract]:Dam deformation monitoring is an important monitoring project of dam safety monitoring and plays an important role in reservoir flood control safety. With the rapid development of 3D laser scanning technology, it provides new technical support for dam deformation monitoring. 3D laser scanning can obtain abundant and complete 3D point cloud data, image data, reflection intensity and other information, and has the characteristics of high efficiency, high accuracy and initiative, which makes it can be used in dam deformation monitoring. This paper focuses on 3D deformation analysis of earth-rock dam, from point cloud data collection, processing to dam deformation analysis, trying to solve the key technical problems of 3D laser scanning technology applied in dam deformation monitoring. Three-dimensional laser scanning technology has broken the limitation of traditional one-dimensional dam deformation monitoring at single point. In order to improve the accuracy and reliability of dam deformation monitoring and analysis, the three-dimensional and integral analysis of dam deformation monitoring and analysis is helpful to improve the accuracy and reliability of dam deformation monitoring and analysis. It provides a more reliable scientific basis for dam safety assessment. This paper starts with the technology and method of dam deformation monitoring based on point cloud data and focuses on improving the accuracy and efficiency of deformation monitoring of earth-rock dams. In order to improve the accuracy and efficiency of point cloud data stitching for multi-station massive dams, the point cloud data automatic splicing technology of multi-station massive dams based on spherical target is studied. The indexing method of organizing and managing massive point cloud data and the fitting algorithm of sphere target are solved. The experiment results show that the method has high splicing efficiency and precision. Dam deformation analysis is the focus and difficulty of this paper. In this paper, the deformation analysis method based on scattered point cloud profile data and the deformation analysis method based on dam precise three-dimensional model are proposed. This paper mainly solves the problem of fitting the section line of scattered point cloud data and the algorithm of deformation analysis, and analyzes the dam deformation through the section data of sequential point cloud. In order to construct the accurate 3D model of the dam, this paper improves the construction of the 3D surface model of the dam based on the adaptive curved volume element, which effectively solves the problems of the low efficiency of the construction network, the void of the surface, the non-uniformity of the normal direction and the overlap of the surface, etc. It lays a good foundation for accurate contrast analysis of dam. On the basis of analyzing and comparing the deformation analysis methods based on adjacent points and C2m (cloud to mesh) based on DEM, the uncertainty of scattered point cloud data sources is fully considered. A multi-scale dam deformation analysis method based on the confidence interval of scattered point cloud roughness is proposed, and the problems of calculating core points, calculating roughness and setting parameters of spatial confidence interval at different scales are solved. The feasibility and effectiveness of the method are verified by experimental analysis. The accuracy of the method is verified by comparing it with the deformation analysis method based on the accurate 3D model of the dam.
【学位授予单位】：郑州大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TV698.11

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