Open Access

ARTICLE

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

L. Yu^1,2,3, P. Sun^1,2,3, S. Han^1,2,3, X. Tong^1,2,3, P. Peng^1,2,3

1 Key Laboratory of Intelligent Processing Technology and Equipment of Fujian Province, Fuzhou, Fujijan 350118 China
2 Numerical Control Equipment Industry Technology Innovation Institute of Fujian Province, Fuzhou, Fujijan 350118 China
3 School of Mechanical and Automotive Engineering, Fujian University of Technology, Fuzhou, Fujijan 350118 China

* Corresponding Author: L. Yu ()

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería 2023, 39(4), 1-10. https://doi.org/10.23967/j.rimni.2023.10.007

Accepted 23 October 2023; Issue published 14 November 2023

Abstract

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.

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Keywords

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