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| Response surface method optimization analysis of cyclonic continuous centrifugal separator for hematite classification |
| Received:March 07, 2022 Revised:March 22, 2022 |
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| DOI： |
| KeyWord:hematite; cyclonic continuous centrifugal separator; classification; response surface methodology |
| Author | Institution |
| ZhangPei |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
| Xie Haiyun |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
| Li Yuanhong |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
| Chen Luzheng |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
| JIN Yanling |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
| Chen Jialing |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
| ZengPeng |
Faculty of Land and Resources Engineering, Kunming University of Science and Technology |
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| Abstract: |
| The cyclone continuous centrifugal sorter is a new type of sorting equipment developed based on the cyclone centrifugal separation technology and fluidized bed sorting principle. The study used the cyclone continuous centrifugal sorter to conduct the classification test for hematite ore, and analyzed and determined the main influencing factors and optimal process parameters for different particle size of hematite ore classification. Based on the experimental study, the influence of the interaction between the process parameters of the cyclone continuous centrifugal sorter on the classification efficiency of hematite ore was analyzed by response surface method, and the parameters were optimized, and the optimized process conditions were 51.35 kPa feed pressure, 12.14 kPa backwash water pressure, and 32.27 kPa bottom flow port pressure, under which the experimental verification obtained the coarse particle size (+0.074~-0.15mm) and fine-grained (-0.074mm) hematite ore were 68.19% and 53.12%, respectively, which were in good agreement with the predicted values and had a good classification effect. This study provides some reference and reference for the application of response surface method to the classification of hematite and other ores. |
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