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Title: Measurement of the phosphorite ore pulp density based on the image recognition method

Authors: Xianhai Li; Han Li; Jiying Zhang; Fan Zhou; Aoao Chen

Addresses: Mining College, Guizhou University, Guiyang 550025, China; National and Local Joint Laboratory of Engineering for Effective Utilization of Regional Mineral Resources from Karst Areas, Guiyang 550025, China; Guizhou Key Lab of Comprehensive Utilization of Non-metallic Mineral Resources, Guiyang 550025, China ' Mining College, Guizhou University, Guiyang 550025, China; National and Local Joint Laboratory of Engineering for Effective Utilization of Regional Mineral Resources from Karst Areas, Guiyang 550025, China; Guizhou Key Lab of Comprehensive Utilization of Non-metallic Mineral Resources, Guiyang 550025, China ' Mining College, Guizhou University, Guiyang 550025, China; National and Local Joint Laboratory of Engineering for Effective Utilization of Regional Mineral Resources from Karst Areas, Guiyang 550025, China; Guizhou Key Lab of Comprehensive Utilization of Non-metallic Mineral Resources, Guiyang 550025, China ' Mining College, Guizhou University, Guiyang 550025, China; National and Local Joint Laboratory of Engineering for Effective Utilization of Regional Mineral Resources from Karst Areas, Guiyang 550025, China; Guizhou Key Lab of Comprehensive Utilization of Non-metallic Mineral Resources, Guiyang 550025, China ' Mining College, Guizhou University, Guiyang 550025, China; National and Local Joint Laboratory of Engineering for Effective Utilization of Regional Mineral Resources from Karst Areas, Guiyang 550025, China; Guizhou Key Lab of Comprehensive Utilization of Non-metallic Mineral Resources, Guiyang 550025, China

Abstract: In this paper, the image recognition method was applied to determine the phosphorite ore pulp density in the field of mineral processing engineering. The self-designed image recognition method-based ore pulp density measurement system was used to measure the density of phosphate ore pulp and conduct the feasibility analysis. The test results indicate that the grey value of phosphate ore pulp with different densities matched well with the pulp value. The test error of the ore pulp density of phosphate ore was 0.72%-1.23%, which could basically satisfy the requirements of industrial application with little discreteness, high accuracy and high precision. This study proves that it was feasible to measure phosphate ore pulp density by using an image recognition method and provides a new idea for ore pulp density measurement and some thoughts for the application of image recognition in mineral processing engineering.

Keywords: image recognition; phosphorite ore; characteristic colour; exponential approximation curve; ore pulp density.

DOI: 10.1504/IJMME.2022.124147

International Journal of Mining and Mineral Engineering, 2022 Vol.13 No.1, pp.64 - 75

Accepted: 20 Apr 2022
Published online: 14 Jul 2022 *

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