Point cloud simplification algorithm based on particle swarm optimization for online measurement of stored bulk grain

The simplification of 3D laser scanning point cloud is an important step of surface reconstruction and volume estimation of bulk grain in granary.This study presented an adaptive simplification algorithm based on particle swarm optimization(PSO).It introduced PSO into the average distance method,a conventional simplification method.The basic idea of this algorithm was to adaptively determine the optimal point reducing intervals of scanning lines according to original point cloud density by PSO.By using the 3D point cloud scanned from bulk grain surface in granary,the proposed algorithm was validated.Compared with the average distance method,the proposed algorithm obtained more evenly distributed point set,smaller reduction ratio(6.96%)and higher volume estimation accuracy(relative error was less than 3‰).The 3D laser scanner(GSLS003,Jilin University and SkyViTech Co.,Ltd.,Hangzhou,China)used in this study could scan the complete picture of the grain surface in a granary in one time,so the acquired point cloud data do not have to be jointed.For the good simplification performance and capability of updating the reducing interval at any moment,the proposed algorithm and the 3D laser scanner could be used to realize online real-time measurement of stored bulk grain volume in granary.

Design and experiment of a subsoiling variable rate fertilization machine

In order to improve soil fertility and fertilizer utilization,a subsoiling variable rate fertilization machine based on conservation tillage and precision agriculture was designed and tested.The relationship between suspension parameters and penetrating distance was analyzed,and a matching model between fertilizing quantity and penetrating distance was established.The variable rate fertilization control machine was developed based on an Advantech PCM-9363 industrial control mainboard.The machine operates under two patterns:DGPS-based positioning and straight-line path positioning based on a planar coordinate system.This machine can perform on-demand fertilization according to the spatial differences in soil nutrients and the prescription maps pre-set before the operation.Field experiments showed the machine has a subsoiling stability of 92.5%,a soil breaking rate of 61.1%,a maximum positioning relative error of 2.68%and a maximum variable rate fertilization error of 3.89%.The subsoiling performance and variable rate fertilization indices of this machine satisfy the requirements of GB/T24675.2-2009.The tested indices meet the national and industrial standards and satisfy the design requirements.The findings of the research can be used as the structural design of the subsoiling variable rate fertilization machine.