基于层次分析法的大型半自磨机磨矿性能优化

为提升大型半自磨机的磨矿性能,建立了半自磨机离散元模型,将离散元仿真结果和试验测试结果进行了对比,验证了所建离散元模型的合理性。在此基础上,研究了影响磨矿性能的主要因素及其影响规律,应用层次分析法构造了因素与指标之间的层次结构和判断矩阵,建立了磨矿性能评价指标预测模型。应用该模型优化了某大型半自磨机的主要磨矿性能影响因素,与优化之前对比,比功率和钢球与矿料总有效碰撞次数分别提高了10.78%、15.47%,衬板最大磨损高度降低了10.81%,综合磨矿性能提高了17.25%。

Optimization of Grinding Performance for Large-type Semi-autogenous Mill Based on Analytic Hierarchy Process

In order to improve the grinding performance of large-type semi-autogenous (SAG) mill, the trajectories of steel balls under different filling numbers were obtained through the test of the test bench of mill. Discrete element equivalent model of test bench was built and the trajectories of the steel balls were simulated. Test results and simulation results of equivalent model were compared. The comparisons showed that test results of trajectories of steel balls were consistent with simulation results. The main factors influencing the grinding performance and the influence law were studied. Mathematical model between factors and evaluation indexes was obtained through the quadratic polynomial stepwise regression analysis and analysis of variance. Optimal parameters combination was also obtained. The hierarchy structure and judgment matrix between factors and indexes were created by using the analytic hierarchy process. The prediction model of comprehensive evaluation index of grinding performance was established, by which the main design parameters of large-type SAG mill were optimized. Compared with the index values before optimization, the power per unit mass and total effective collision frequency between steel balls and aggregates were increased by 10.78% and 15.47%, respectively, and the maximum wear height of the lining was decreased by 10.81%. Meanwhile, the comprehensive grinding performance was increased by 17.25%.