一种基于点云法向量的基准特征提取与倾斜分析方法

A datum feature extraction and deformation analysis method based on normal vector of point cloud

针对目前将三维激光扫描技术应用于变形监测领域存在基准特征难以提取、点云数据分析缺乏适用的方法等问题,本文提出了一种基于点云法向量的基准特征提取与形变分析方法。首先利用局部平面拟合方法获得点云的法向量,并沿点云法矢方向探测基准点;然后利用三次B样条曲线对探测的正确基准点进行拟合;最后根据拟合曲线计算基准高程和对径点倾斜角分析基准特征形变信息。对某化工厂的罐体点云数据进行基准特征提取结果表明,该方法可以快速、全面地获取监测对象的整体信息,且能够正确分析监测对象的基准形变。

In order to solve the problems of the existing difficulty of datum feature extraction and the lack of applicable analysis method of point cloud data in the application of three-dimensional laser scanning technology to the field of deformation monitoring,an efficient method for datum feature extraction and deformation analysis is proposed in this paper based on normal vector of point cloud. Firstly,owing to the local surface fitting obtains directly the geometric features by applying the point cloud model with low time complexity,this paper uses the local planar normal vector determined by the nearest neighbours of meet certain condition and follow the normal vector of the point cloud to detect the datum points. Then,the cubic B-spline curve fitting is performed on the datum points. To this end,elevation of the datum and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information is analyzed. The proposed approach is verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively,and reflect the datum deformation accurately.