集料颗粒的棱角性是决定沥青混合料路用性能的重要因素。文中首先搭建了基 于 Gocator 3D 智能传感器的集料三维图像采集系统，获取粒径为 9. 5、13. 2 和 16. 0 mm 的玄武岩、花岗岩和石灰岩3 种集料样本的三维点云数据; 然后采用基于 Sobel-Feldman 卷积和基于集料表面法线的集料颗粒表面棱角性量化方法进行评价，并与现有 AIMS 梯 度棱角评价方法进行了对比。结果表明: 基于 Sobel-Feldman 卷积的集料颗粒表面棱角 性量化方法评价集料颗粒棱角性具有更高的准确性; 集料越尖锐，集料棱角性指数越 大，法线聚类个数越多; 集料越圆滑，集料棱角性指数越小，法线聚类个数越少。

The angularity of the aggregate particles is an important factor determining the performance of asphalt mixes for road use． In this paper，firstly，a 3D image acquisition system based on Gocator 3D intelligent sensor was built to obtain 3D point cloud data of 3 aggregate samples of basalt，granite and limestone with particle sizes of 9. 5 mm，13. 2 mm and 16. 0 mm． Then，the Sobel-Feldman convolution method and the aggregate surface normal method was used to evaluate the surface angularity of aggregate particles，and the two methods were compared with the existing AIMS gradient angularity evaluation method． The results show that the quantitative method of aggregate particle surface angularity based on Sobel-Feldman convolution is more accurate． In addition，the sharper the aggregate is，the larger the laggregate angularity index and the number of normal clusters are; the more round the aggregate is，the smaller the aggregate angularity index and the number of normal clusters are．