基于数据建模的旋流器分级效率优化研究与应用

Research and Application of Cyclone Classification Efficiency Optimization Based on Data Modeling

旋流器是矿山磨矿分级系统的重要设备,关系到选矿效率和质量。由于给矿泵池液位波动频繁,会出现生产指标频繁波动的情况,影响分级效率。通过大数据应用,发现传统旋流器分级控制方法存在的不足及原因,通过优化旋流器分级控制方法,保证了现场工况的持续稳定。应用数据建模与机理建模相结合,依托数据分析平台,实现了旋流器分级系统多维度数据模型支持下的现场参数优化,以及建立旋流器分级系统物理设备和工艺的数字化映射,更加真实反映了现场的工况,对各矿山选厂分级系统有广泛的借鉴意义。

Cyclone is an important equipment of mine grinding classification system,which is related to the efficiency and quality of mineral processing.Due to the frequent fluctuation of the liquid level of the feed pump pool,the classification efficiency is affected,and the production index will fluctuate frequently.Through the application of big data,the shortcomings and causes of the traditional cyclone grading control method are found.By optimizing the cyclone grading control method,the continuous stability of the field conditions is ensured.By combining data modeling and mechanism modeling,relying on the data analysis platform,the field parameter optimization supported by the multi-dimensional data model of the cyclone classification system is realized,and the digital mapping of the physical equipment and process of the cyclone classification system is established,which more truly reflects the working conditions of the site,and has a wide range of reference significance for the classification system of each mine concentrator.