大型椭球类复杂曲面仿形加工点云数据去噪光顺算法

Denoising and smoothing algorithm of point cloud data for profiling of large ellipsoid complex curved surface

针对装备制造、航空航天等领域中许多高性能要求的大型椭球薄壁类零/部件在仿形加工过程中数据量大、工件表面细微特征复杂的加工难点,提出了一种大型椭球类复杂曲面仿形加工点云数据去噪光顺算法。去噪光顺算法利用S-H-ESD(Seasonal-Hybrid-ESD)算法将点云数据分解,以进行噪声点的识别与光顺,然后利用改进后的双边滤波算法对点云数据进行整体光顺。最后通过实验,以某装备制造现场采集的大型球冠工件点云数据作为实验对象,证明了该算法能够快速有效地进行大型椭球类复杂曲面点云数据的去噪与光顺。

Aiming at the difficulties of large amount of data and complex subtle features on the surface of the workpiece in processing large ellipsoid thin-walled parts/components required by high performance,which are in the fields of equipment manufacturing,aerospace and other fields,proposed a denoising and smoothing algorithm of point cloud data of profiling for large ellipsoid complex surfaces.The denoising smoothing algorithm uses the S-H-ESD(Seasonal-Hybrid-ESD)algorithm to decompose the point cloud data to identify and smooth the noise points,and then uses the improved bilateral filtering method to smooth the surface data as a whole.Finally,through experiments,using the point cloud data of large spherical crown workpieces collected at a certain equipment manufacturing site as experimental objects,it is proved that the denoising and smoothing algorithm can quickly and effectively de-noise and smooth large ellipsoid surface data.