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| Study on Prediction Model of High Silicon Magnetite Selectivity |
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Received:September 20, 2022
Revised:October 17, 2022
Accepted:October 19, 2022
Published Online:April 21, 2023
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| DOI： |
| KeyWord:high silicon iron concentrate; prediction of optionality; process mineralogy; correlation |
| Author | Institution |
| zhuxinzhou |
Yangzhou Pacific Special Materials Co.，Ltd. |
| linkun |
School of Minerals Processing and Bioengineering, Central South University |
| wunanyong |
Yangzhou Pacific Special Materials Co.，Ltd. |
| chenfang |
Yangzhou Pacific Special Materials Co.，Ltd. |
| suzijian |
School of Minerals Processing and Bioengineering, Central South University |
| zhangyuanbo |
School of Minerals Processing and Bioengineering, Central South University |
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| Abstract: |
| China's iron ore resources are abundant, but the external dependence is high due to the low grade and complex composition. In recent years, with the depletion of high-quality low silica iron ore resources worldwide, the price of imported iron ore has been rising. In order to meet the needs of domestic steel production, the use of rich reserves and low prices of high silica iron ore concentrates as a source of iron and steel production is of great strategic importance. Based on the process mineralogical study of high silica iron ore concentrate in a plant, it was found that the distribution pattern of Fe and Si elements in different particle sizes differed, and the beneficiation index of ore samples with high distribution rate of SiO2 in +20μm particle size was low, while the concentrate grade of ore samples with high grade of TFe in -20μm particle size was higher after magnetic separation and showed a linear correlation. The mathematical model of Fe and Si distribution rate is established by using statistical techniques, and the correlation between Fe and Si content and Fe and Si distribution rate is determined by regression analysis and significance test, which is of great significance to guide the beneficiation and pellet production. |
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