Traffic & Transportation Engineering

Quantitative Evaluation for Aggregate Particle Angularity Based on 3D Point Cloud Data

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  • School of Information Engineering,Chang'an University,Xi'an 710064,Shaanxi,China
郝雪丽 ( 1987-) ,女,博士,高级工程师,主要从事路用材料性能分析、机器学习、人工智能在道路施工质 量过程控制中的应用研究。E-mail: xuelihao_lucky@126.com

Received date: 2020-05-19

  Revised date: 2020-08-18

  Online published: 2021-01-01

Supported by

Supported by the National Natural Science Foundation of China ( 51908059,51978071) and the National Key R&D Program of China ( 2018YFB1600202)

Abstract

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.

Cite this article

HAO Xueli, SUN Zhaoyun, GENG Fangyuan, et al . Quantitative Evaluation for Aggregate Particle Angularity Based on 3D Point Cloud Data[J]. Journal of South China University of Technology(Natural Science), 2021 , 49(1) : 142 -152 . DOI: 10.12141/j.issn.1000-565X.200251

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