Parameter selection and experimental study of the rock particle crushing effect using an image-based method

被引:0
作者
Yu, L. [1 ,2 ,3 ]
Sun, P. [1 ,2 ,3 ]
Han, S. [1 ,2 ,3 ]
Tong, X. [1 ,2 ,3 ]
Peng, P. [1 ,2 ,3 ]
机构
[1] Key Lab Intelligent Proc Technol & Equipment Fujia, Fuzhou 350118, Fujijan, Peoples R China
[2] Numer Control Equipment Ind Technol Innovat Inst F, Fuzhou 350118, Fujijan, Peoples R China
[3] Fujian Univ Technol, Sch Mech & Automot Engn, Fuzhou 350118, Fujijan, Peoples R China
来源
REVISTA INTERNACIONAL DE METODOS NUMERICOS PARA CALCULO Y DISENO EN INGENIERIA | 2023年 / 39卷 / 04期
关键词
NC-SA license; Image processing; Rock particles; Crushing effect parameters; Loading mode; Feed particle size; SHAPE; SIZE;
D O I
10.23967/j.rimni.2023.10.007
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
When maging is used to detect the crushing effect of rock particles, the selected characterization parameters are important factors affecting the results. The image-based detection system is composed of three parts: an image acquisition system, a storage platform, and a digital image processing system.The influence of loading mode and feeding particle size on rock crushing degree and rock morphology characteristics after crushing are analyzed respectively; The crushing ratio and sand-forming ratio of limestone, limestone and granite under shear and extrusion loads are analyzed. The experimental results show that the crushing ratio and sand formation rate play a key role in the crushing of rocks composed of different materials under shear compression loading. The effect analysis of crushing under the feed particle size of 9.5 mm to 16mm shows that there is a great correlation between edges and corners, roundness and overall contour. It provides a basis for the follow-up research on intelligent mine construction and equipment optimization, and is worthy of further popularization and application.
引用
收藏
页数:10
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