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矿石智能分选机执行子系统仿真及参数多目标优化

Simulation and parameter multi-objective optimization of execution subsystem of ore intelligent sorter

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【作者】 冯啟轩张怀亮王周闵湘川

【Author】 FENG Qixuan;ZHANG Huailiang;WANG Zhou;MIN Xiangchuan;School of Mechanical and Electrical Engineering, Central South University;State Key Laboratory of High Performance and Complex Manufacturing, Central South University;Hunan Jumper Technology Co.Ltd.;

【通讯作者】 张怀亮;

【机构】 中南大学机电工程学院中南大学高性能复杂制造国家重点实验室湖南军芃科技股份有限公司

【摘要】 为改善矿石智能分选机执行子系统的工作性能,提高矿石分选的效率和准确率,提出基于多目标粒子群算法的矿石智能分选机执行子系统参数优化方法。基于CFD软件对矿石智能分选机空气喷嘴的气流进行仿真,采用MATLAB软件对矿石分选过程建立仿真模型,并通过高速相机拍摄矿石运动轨迹验证模型的准确性。应用正交旋转组合设计方法设计试验组合,仿真分析所选水平内气嘴角度、气嘴间距、气嘴直径、气嘴与滚筒距离、分界挡板与滚筒距离、喷吹气压以及喷吹高度这7个因素对夹带率和执行率的影响,并建立夹带率和执行率数学回归模型。以夹带率和执行率数学回归模型为目标函数,降低夹带率和提高执行率为优化目标,运用多目标粒子群优化算法进行参数优化。研究结果表明:参数优化后,设备的夹带率降低了3.19%,执行率提高了2.16%,对提高分选机工作效率和经济效益有着重要意义。

【Abstract】 In order to improve the performance of the execution subsystem of the ore intelligent sorting machine and improve the efficiency and accuracy of ore sorting, a parameter optimization method for the execution subsystem of the ore intelligent sorting machine based on the multi-objective particle swarm algorithm was proposed. Based on CFD software, the air flow of the air nozzle of the ore intelligent sorting machine was simulated. MATLAB software was used to establish a simulation model of the ore sorting process, and the accuracy of the model was verified by photographing the ore movement trajectory with a high-speed camera. The orthogonal rotation combination design method was used to design the test combination, and the influence of the selected horizontal inner air nozzle angle, air nozzle spacing, air nozzle diameter, distance between the air nozzle and the drum, distance between the dividing baffle and the drum, injection air pressure and injection height on the entrainment rate and execution rate were simulated and analyzed, and a mathematical regression model of the entrainment rate and execution rate was established.Taking the mathematical regression model of entrainment rate and execution rate as the objective function, reducing the entrainment rate and increasing the execution rate as optimization goals, multi-objective particle swarm optimization algorithm was used to optimize the parameters.The results show that the original equipment’s entrainment rate is reduced by 3.19%, and the execution rate is increased by 2.16%. The optimal solution is of great significance for improving the working efficiency and economic benefits of the sorting machine.

【基金】 国家重点研发计划项目(2023YFC3904204)~~
  • 【文献出处】 中南大学学报(自然科学版) ,Journal of Central South University(Science and Technology) , 编辑部邮箱 ,2024年10期
  • 【分类号】TD45;TP391.9
  • 【下载频次】48
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