Study On Intelligent Control System Of Multi-cylinder Hydraulic Cone Crusher

With the rapid development of industry,hydraulic cone crusher plays an important role in industry.Hydraulic cone crusher is an important equipment widely used in metallurgy,mining,chemical industry,electric power,ceramics,cement,construction and road construction sectors.Material crushing plays an important role in mineral processing industry.Therefore,the cone crushing control system is studiedin this paper,and the existing control method is improvedaccording to the current research results.Firstly,the factors affecting the crushing force of the cone crusher are studied.Through the analysis of ore properties,particle size distribution coefficient,compression ratio of cone crusher crushing force has a major impact,and then establish the crushing force mathematical model.The calculated crushing force is applied to each layer of the cone crushing mobile cone.The purpose of calculating the maximum stress and deformation of the moving cone is to provide reliable boundary conditions for the subsequent control system,so as to prevent the damage of the moving cone caused by the excessive load and the occurrence of abnormal working conditions.Secondly,the ore particle size of the ore produced was detected,and the method of soft measurement based on least squares support vector machine was used to detect the ore particle size online.Firstly,the selection of auxiliary variables.Secondly,the acquisition of auxiliary variable data.The data of the acquired auxiliary variables are preprocessed.Then,the method of multi-rate digital signal processing is used to process the data,so as to unify the periods of different data collected at different time.Thirdly,PCA(Principal Component Analysis)technology was used to conduct dimensionality reduction processing on the data,with the purpose of eliminating the data with relatively large correlation.Finally,a soft measurement model based on least square support vector machine is established.Thirdly,the input boundary conditions of the control system is studied,that is,the intelligent setting method of material crushing.The purpose of this method is to set the target value intelligently so that the target value satisfies the boundary condition.First,the method of case-based reasoning is used as the preset model of the control loop,and the target value of gravel particle size and boundary condition are used as the input values of the preset model of the control loop to obtain a new output value.Then the neural network-based machine learning method is used as the feedforward and feedback compensation algorithm to obtain the compensation values..The current control quantity of the control system is the sum of the output value and the compensation values of the former feedback and negative feedback.Then,the controller of the control system is studied,that is,the intelligent coordinated control system of the cone crusher crushing process.Firstly,the method based on T-S fuzzy controller is used as the controller in normal operating condition to obtain the output value.Secondly,the controller based on random configuration network is used as the controller of abnormal condition to obtain an output value.Finally,the coordination factor method based on the fuzzy model is used as the switching mechanism of the control system.This model calculates the coordination factor according to the relationship between the parameters of the current crusher and the material feed amount.Then calculate the actual output value of each controller according to the coordination factor,and finally get the total output quantity.