基于改进的角度偏差法的采空区点云数据精简

在保证采空区几何特征不变的前提下,有必要对点云数据进行精简,提高三维建模及其应用的效率。介绍了点云数据精简算法的评价体系,探讨了空区探测系统扫测采空区的点云数据特点; 在对比最小距离法、平均距离法、角度偏差法、弦高偏差法等采空区点云数据精简方法的基础上,提出了保留采空区几何特征更为有效的点云数据精简方法——改进的角度偏差法。通过对比精简前后的扫描线周长、面积及标准差等指标,认为该方法不但保持了扫描线的细节,而且使精简后扫描线上的点分布较均匀,为后续三维建模及应用打下良好基础。

Study on Point Cloudy Data Simplification of Goaf Based on Improved Angular Deviation Method

It is necessary to simplify point cloudy data in order to improve 3D modeling and its application on the condition of remaining the geometric feature of goaf. The evaluation system for point cloud data simplification algorithm was introduced, and the characteristics of point cloudy data of goaf scanned by cavity monitoring system were discussed; according to the comparison with point cloud data simplification algorithms including minimum distance method, average distance method, angular deviation method and chord height deviation method, improved angular deviation method, which was more effective to remain the geometric feature of goaf, was proposed. Compared with the perimeter, area and standard deviation of scan lines before and after simplification, the results showed that improved angular deviation method not only remained the details of scan lines, but also uniformed the points on the simplified scan lines. The improved angular deviation method could lay a good foundation for the subsequent 3D modeling and its application.