| Zhengzhou Institute of Multipurpose Utilization of Mineral Resources, Chinese Academy of Geological Sciences | Host |
| Citation: |
XIAO Qingfei, SUN Boyuan, JIN Saizhen, WU Yukai, WANG Mengtao. Grinding Medium Optimization Based on Grinding Kinetics and Discrete Element Analysis[J]. Conservation and Utilization of Mineral Resources, 2025, 45(1): 28-38. doi: 10.13779/j.cnki.issn1001-0076.2024.08.019
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Grinding Medium Optimization Based on Grinding Kinetics and Discrete Element Analysis
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Abstract
In this study, the effects of steel balls and steel cylpebs as the grinding media on the crushing behavior and energy utilization of multi−grain ores were investigated using grinding dynamics and discrete element method (DEM) simulation, and industrial experimental research was carried out based on the results. The results of grinding kinetics show that the effect of steel balls on the crushing rate of the coarse grain fraction was better than that of steel cylpebs. The content of +0.15 mm in the grinding product is reduced by 0.98% and −0.074 mm increased by 5.66% in the case of steel ball compared with that of steel cylpebs as the grinding medium. DEM analysis showed that the motion state of steel balls was more active than that of steel cylpebs. The percentage of energy used for ore crushing using steel balls and steel cylpebs as the grinding medium was 65.41% and 61.29%, respectively, with the former being 4.12% higher than the latter so that the effective energy utilization of steel balls for crushing the ore is higher. Based on the above results, after using steel balls as grinding media in the Dahongshan Iron Mine, the overflow −0.074 mm content of the cyclone increased from 74.00% to 81.71%, an increase of 7.71%, the unit steel consumption decreased by 9.52%, from 0.63 kg/t to 0.57 kg/t, and the unit power consumption decreased by 11.61%, from 11.46 kW·h/t to 10.13 kW·h/t. This study verified the validity of the steel ball scheme through grinding dynamics and discrete element analysis experiments and verified its accuracy through industrial tests.
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References
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XIAO Qingfei, SUN Boyuan, JIN Saizhen, WU Yukai, WANG Mengtao. Grinding Medium Optimization Based on Grinding Kinetics and Discrete Element Analysis[J]. Conservation and Utilization of Mineral Resources, 2025, 45(1): 28-38. doi: 10.13779/j.cnki.issn1001-0076.2024.08.019
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Figure 1.
Particle size characteristic curve (a—cyclone feeding; b—cyclone sedimentation; c—cyclone overflow; d—ball mill discharge)
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Figure 2.
Mill cylinder structure model
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Figure 3.
Crushing behavior of different size steel balls on iron ores with different particle sizes (a—Ф50 mm steel ball; b—Ф40 mm steel ball; c—Ф30 mm steel ball; d—Ф20 mm steel ball)
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Figure 4.
Effect of ore feeding size on specific crushing rate under different sizes of steel balls (a—Ф50 mm steel ball; b—Ф40 mm steel ball; c—Ф30 mm steel ball; d—Ф20 mm steel ball)
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Figure 5.
Crushing behavior of different size steel cylinder on iron ores with different particle sizes (a—D×L 45 mm×50 mm; b—D×L 35 mm×40 mm; c—D×L 30 mm×35 mm; d—D×L 20 mm×25 mm)
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Figure 6.
Effect of ore feeding size on specific crushing rate under different sizes of steel cylinder (a—D×L 45 mm×50 mm; b—D×L 35 mm×40 mm; c—D×L 30 mm×35 mm; d—D×L 20 mm×25 mm)
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Figure 7.
Particle motion status under different media schemes (a—steel ball; b—steel cylpebs)
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Figure 8.
Particle collision energy spectra for different media schemes
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Figure 9.
Steel ball consumption during industrial testing
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Figure 10.
Steel ball consumption during industrial testing