基于CFD-DEM耦合的矿石智能分选机一分三执行机构参数优化OA

To enhance the working performance of the three-way actuator of the intelligent ore sorting machine,a parameter optimization method for the actuator based on CFD-DEM coupling was proposed.A gas nozzle flow field model was established based on computational fluid dynamics(CFD),and a mineral particle model was established using the discrete element method(DEM).The CFD-DEM coupled model was used to simulate the precise blowing of ore by the gas nozzles.The trajectory of the ore after leaving the gas flow field was predicted using the MATLAB program.The correctness of the model was verified by comparing the prediction results with the experimental measurement results.Through single-factor simulation analysis,the influence of 10 factors,including the upper and lower gas nozzle angles,the distance between the upper and lower gas nozzles and the drum,the blowing height of the upper and lower gas nozzles,the distance between the front and rear boundary baffles and the drum,and the blowing pressure of the upper and lower gas nozzles on the concentrate execution rate,tailings execution rate,concentrate bin carryover rate and tailings bin carryover rate was obtained,and the response surface regression models of the execution rate and carryover rate were established.With the optimization goal of improving the concentrate and tailings execution rates and reducing the concentrate and tailings bin carryover rates,the optimal parameter combination was obtained using the MOPSO algorithm.Compared with the original equipment,after optimization,the concentrate execution rate of the actuator is increased by 12.68%,the tailings execution rate is increased by 2.23%,the concentrate bin carryover rate is reduced by 1.76%,and the tailings bin carryover rate is reduced by 0.36%,which is of great significance for enhancing the sorting accuracy and efficiency of the sorting machine.