Comparison of the different mathematical methods performed in determining the size distribution of aggregates using LiDAR point cloud data and suggested algorithm

A number of methods and machines based on these methods have been developed to determine particle size. Image analysis has been used for many years to determine the particle size distribution of materials especially relatively coarse sized, in large quantities, or spread over a large area where screen analysis cannot be applied. The three-dimensional data supporting the classical digital image analysis method working with two-dimensional data were recently introduced to increase the accuracy of the analysis results. In this study, the piles formed by aggregate mixtures with known particle size distributions were scanned with terrestrial laser scanner to obtain point cloud data and then the particle size distributions of these piles were determined with the help of the algorithm given here. An important step of the algorithm used is to determine the local minimum points on the scan surfaces. Three different mathematical methods have been used at this stage. When the particle size distribution curves obtained by sieve analysis of the mixtures are taken into consideration, the most accurate result is obtained in the morphological reconstruction approach. It has been concluded that the particle size distributions of the aggregate piles can be reliably determined with the use of the point cloud data and the algorithm using that approach.