| 基于点云密度特征的滑坡位移监测方法 |
| |
| 引用本文： | 刘卫南,谢谟文.基于点云密度特征的滑坡位移监测方法[J].岩土力学,2020,41(11):3748-3756. |
| |
| 作者姓名： | 刘卫南 谢谟文 |
| |
| 作者单位： | 北京科技大学 土木与资源工程学院，北京 100083 |
| |
| 基金项目： | 家自然科学基金资助项目（No. 41572274） |
| |
| 摘 要： | 激光扫描仪对同一目标两次采集的点并不重合，无法通过点云的直接比较快速确定滑坡位移。考虑到单个点云位置的不确定性和区域点云密度的稳定性，将点云的密度作为滑坡表面变形的表征，提出了基于点云密度特征的滑坡位移监测方法。将离散的三维点云转化为二维的密度图像，再利用粒子图像测速技术分析位移前后两幅点云密度图像的相关性，从而计算栅格图像中各子集的相对位移值；当各子集的位移全部计算完成后，得到目标区域的平面位移场。室内块体移动试验表明该方法的计算精度受变形梯度的影响，在地表变化剧烈处会产生一定程度的误差，且子集相关性系数无法达到1。在黄藏寺滑坡的位移监测中，利用本方法识别出了边坡的变动区域，计算出了滑坡的平面位移场，直观地反映了滑坡表面变形状况，验证了该方法的实用性。
|
| 关 键 词： | 三维激光扫描 粒子图像测速 滑坡监测 点云比较 |
| 收稿时间： | 2020-03-01 |
| 修稿时间： | 2020-04-13 |
Landslide monitoring based on point cloud density characteristics |
| |
| LIU Wei-nan,XIE Mo-wen.Landslide monitoring based on point cloud density characteristics[J].Rock and Soil Mechanics,2020,41(11):3748-3756. |
| |
| Authors: | LIU Wei-nan XIE Mo-wen |
| |
| Institution: | School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China |
| |
| Abstract: | It has been realized that the points collected twice by the laser scanner for the same target do not coincide, and the landslide displacement cannot be quickly determined by direct comparison of the point cloud. Because the position of a single point cloud is uncertain and the density of regional point clouds is stable, the density of the point cloud can be used as the characterization of the deformation of the landslide surface. The article proposes a landslide displacement monitoring method based on point cloud density characteristics. First, the discrete three-dimensional point cloud is converted into a two-dimensional density image. Then, the particle image velocimetry technique is used to analyze the correlation between the two point cloud density images before and after displacement, thereby to calculate the relative displacement value of each subset in the raster image. When the entire displacements of each subset are calculated, the plane displacement field of the target area is obtained. The indoor block movement test shows that the calculation accuracy of this method is affected by the deformation gradient, which will produce a certain degree of error at the place where the ground surface changes drastically, and the subset correlation coefficient cannot reach 1.0. In the displacement monitoring of the Huangzangsi landslide, the method was used to identify the changing area of the slope, and the plane displacement field of the landslide was calculated. The calculation results intuitively reflect the deformation of the landslide surface, which verifies the practicability of the proposed method. |
| |
| Keywords: | 3D laser scanning technology particle image velocity measurement landslide monitoring point cloud comparison |
|
| 点击此处可从《岩土力学》浏览原始摘要信息 |
| 点击此处可从《岩土力学》下载免费的PDF全文 |
|
