| Cone crusher is the main equipment to crush medium and more hardness mineral It has the advantages of big crushing ratio,high output,low energy consumption and so on.However,with the increasing demand for the quality of the crushed product,the size and shape of the crushed product need to be further improved.Therefore,this paper focuses on improving the crushing performance of cone crusher to increase the output of crushed products,to improve the percentage of the calibration particle size and to reduce the rate of needle.In order to build up the output model of cone crusher,firstly,according to the working principle of the cone crusher and the movement characteristics of the material in the crushing chamber,the three kinds of motion state of the material in the crushing chamber are analyzed;And the critical speed of the moving cone is obtained when the materials are in the state of free falling motion in the crushing chamber;Then the output model of cone crusher is built up combining with the movement distribution of the material in the blocking section.Based on the theory of laminating crushing,the laminating crushing tests were conducted by using the rock mechanics test system.The least square method is used to fit the text data,and the new percentage of the calibration particle size model and the needle rate model are built up.In order to verify the accuracy of the two new models,the GP300 cone crusher crushing the actual output particle size and shape distributions are compared with text results,and it verifies the feasibility and reliability of the two models.Then the prediction and control of particle size and shape will be fulfilledBased on the three models mentioned above,the multi objective optimization function model is built up,whose objective functions are the output of the crusher,the percentage of the calibration particle size,the needle rate.The multi-objective optimization model is transformed into a single objective optimization model with the needle rate being as the main objective function,with the output and the percentage of the calibration particle size being as constraint conditions.In order to verify the accuracy of this single objective model,this paper put GP300 cone crusher as optimization object,then the optimal solution of the model is solved by random direction method.Then the optimal solution are compared with.the parameters before optimization of GP300 cone crusher,and it indicates that the multiobjective optimization model and the calculation method is feasible,which provides a theoretical basis for the optimization of the crushing performance of cone crusher. |
