摘要
随着各地高层构筑物数量的不断增加,构筑物变形产生的安全隐患也不断受到重视。本文针对传统观测方法的局限性和低效性,提出了基于激光散乱点云数据的塔形构筑物倾斜变形监测新方法,采用两台地面激光扫描仪分别扫描构筑物外表面的散乱点云数据,建立塔形构筑物的基础表面模型,生成沿轴线的塔体中心点数据,筛选可靠性最优的线性排列点,从而得出塔形构筑物在空间上高精度的偏移量和倾斜率。最终编程实现了数据获取到成果输出的一键式计算。结果表明,基于点云的塔形构筑物观测结果与传统方法观测结果的角度误差分别为0.005°和0.001°,倾斜量误差分别为0.000 05和0.000 1 m。本文方法可以快速获得构筑物整体和局部的偏移量变化特征,为塔形构筑物的施工、维修和重建提供了基础模型数据。
With the greatly increasing of the tower building from place to place,the potential risk caused by the deformation of the tower building has been taken more and more attention. In view of limitations and inefficiency of the traditional methods,this paper puts forward the new method of inclination monitoring of tower building based on point cloud data generated by 3 D laser scanner. Firstly,we need to capture point cloud of target object using two set of different 3 D laser scanner. Secondly using the point cloud to build tower building ground surface model. Thirdly,generating central point along the axis direction and filtering the correct point group. At last,calculating the offset and amount of inclination with high accuracy of target object. In addition,we also program to realize the output of calculation result just by one key. It turns out that the angle error between the new method and traditional method is separately 0.005°and 0.001°. The amount of inclination is separately 0.000 05 and 0.000 1 m. This method could not only quickly obtain offset variation characteristics of target object and part of them,but also could provide the foundation data model for the construction,maintenance and reconstruction of them.
作者
王娜
段龙飞
徐卫东
王志一
WANG Na;DUAN Longfei;XU Weidong;WANG Zhiyi(China Geological Environment Monitoring, Beijing 100081, China;China University of Mining Technology, Beijing, Beijing 100083, China;Beijing GeoBIM Geomatics Co., Ltd., Beijing 100085, China)
出处
《测绘通报》
CSCD
北大核心
2019年第3期133-136,共4页
Bulletin of Surveying and Mapping
基金
国家重点研发计划(2017YFB0503803)
关键词
塔形构筑物
激光点云
倾斜变形监测
激光扫描仪
倾斜量
tower building
laser point cloud
slope deformation monitoring
laser scanner
amount of inclination