Research On Crushing Behavior And Performance Optimization Of 6-DOF Robotic Crusher

Cone crusher is one of the main equipment for crushing gruanular materials,which is widely used in mining,metallurgy,construction and other industries.Its working environment is harsh,the main parts often work under the condition of high rotational speed and heavy load,which bring on huge energy consumption and steel consumption.In order to save energy and reduce consumption,the optimization design of cone crusher is the key research direction.At present,the optimization design methods are based on the traditional cone crusher.The problems of large energy consumption and wear and the deterioration of crushing chamber size can not be fundamentally avoided.In order to solve the above problems,the 6-DOF robotic crusher has been designed.Its structure and driving mode of moving cone are different from traditional cone crusher.The 6-DOF parallel robot is used to drive the moving cone instead of the spindle and eccentric sleeve in the traditional cone crusher,which can adjust the motion mode of the moving cone in real time.Therefore,the 6-DOF robotic crusher can adjust the moving cone motion mode in real time according to the crushing chamber shape and particle size parameters to achieve the optimal crushing.In this paper,the effects of size parameters of gruanular materials,crushing chamber size parameters and crusher working parameters on crushing behavior,total energy consumption and effective crushing energy consumption,liner wear and throughput of granular materials have been researched.On this basis,the optimal control method of 6-DOF robotic crusher has been obtained.The optimal crushing is achieved by adjusting the precession angle,suspension point position and swing frequency of the mantle under the specific material and crushing chamber.This method is universal and can be extended to the optimal design and control of other crushing equipment.The main research contents include the following aspects:(1)Research on distribution of crushed products.The crushing evolution process of granular materials in the crushing chamber has been researched.The single particle compression ratio has been introduced,and the 3-parameter beta distribution of single particle crushed products has been proposed.Considering the influence of particle size expectation,particle size distribution coefficient,original compression thickness,actual compression ratio and length of closed side on single particle compression ratio of granular material,the function of single particle compression ratio has been established by using discrete element method(DEM)simulation.Based on the above model,the distribution model of crushed products under certain material parameters and crusher parameters has been obtained.(2)Research on energy consumption and liner wear of crusher.The effects of material parameters and crusher size parameters on the stress have been researched by using discrete element method under different simulation conditions.The stress function has been established.Based on this model,the stress and velocity models of each point on the moving cone have been obtained.The energy consumption of crusher and the wear model of mantle liner have been obtained by combining the above models.In the aspect of experimental verification,based on the crushing chamber size,working conditions and feeding distribution data of PYGB1821 cone crusher,combined with crushed products model,energy consumption model and liner wear model,the theoretical crushed products particle size distribution,energy consumption and wear thickness of liner in the whole life cycle under specific conditions were obtained.(3)Research on optimal control of 6-DOF robotic crusher.It provides reference for the real-time adjustment of 6-DOF robotic crusher.The mass fraction of crushed products less than 12 mm,total energy consumption,wear thickness,energy consumption efficiency and throughput have been taken as the performance indexes of 6-DOF robotic crusher.The position of precession angle,suspension point and rotational speed are taken as variables of different working conditions.The crushing chamber is PYGB1821 cone crusher's without wear.The performance index of 6-DOF robotic crusher has been researched under different working conditions.Furthermore,based on the performance index function,the weight of each height is determined by the weight determination method of Fuzzy Multiple Attributes Decision Making,and the equivalent wear model is established.After the above performance indexes are determined,the optimization model of 6-DOF robotic crusher is established.The optimization model optimizes the objective function based on the above performance indexes.The precession angle,the position of the suspension point and the swing frequency of the moving cone are taken as the optimization variables.The optimization function is solved by Gray Wolf Optimization algorithm.The optimal control scheme for specific crushing chamber and material characteristics is obtained.Based on the above research results,the optimal control schemes for different crushing chamber shapes in the whole life cycle of liner have been obtained.Compared with the original scheme,the performance of crusher can be improved obviously.(4)Method promotion research.The above optimization calculation method is promoted to the research of other crushing equipment.Take high pressure roller mill as an example.In the research,the function of single particle crushing product is established.The distribution function and stress function of single particle compression ratio were established under the working conditions of high pressure roll gap,roll diameter and rotational speed.Based on the stress function,the energy consumption and wear function are established.The model is verified by the experimental data of a high pressure roller mill.Finally,particle size,energy consumption and throughput are taken as the optimization objectives.Taking the roll gap,roll diameter and rotational speed of high-pressure roller as optimization variables,the working conditions of high-pressure roller mill with characteristic feed size distribution were optimized.In the optimization scheme,the energy consumption is reduced under the same throughput.