Experimental Parameter Optimization And Intelligent Control Design Of Crushing System

At present,smart agriculture has become an important strategic goal of my country’s modern agricultural development.Accelerating the intelligent technological progress of agricultural and animal husbandry equipment is the necessary way to develop smart agriculture.Hammer mill is the main equipment in feed processing.The overall technical status of feed mill in China is that the degree of automation is low,there is no intelligent models,there is no automatic identification ability for working conditions,the working parameters are relatively single,there is no quantitative real-time matching control model and relevant control theory research between working parameters,and the energy consumption waste is serious.This research group takes the self-developed new hammer mill as the research object,studies and analyzes the influence law of various factors on the performance and finds out the optimal combination of working parameters.A control method based on BP-PID is proposed to meet the adaptive control requirements of feed crusher drive system.The main contents are as follows:(1)Determined the overall test scheme for parameters optimization of crushing system.The hammer mill is made by the research group as the test platform,the working range of each factor is determined,and the five factor,three level and three index orthogonal test table designed by Design Expter13.0 software is used to complete the collection and recording of test data.Then,the response surface analysis is carried out to study the influence of main axis speed,material-returning pipe,feeding rate,mesh aperture diameter and material moisture content on productivity,power consumption per ton and particle size.(2)The optimal working parameter combination is solved and carry out experimental research.Taking productivity,power consumption per ton and particle size as evaluation indicators,the five parameters of main axis speed,material-returning pipe,feeding rate,mesh aperture diameter and material moisture content are tested and analyzed to solve the optimal working parameter combination,and the optimal working parameter combination of feed crusher is experimentally studied.(3)Established the transfer function of the control system.Taking the hammer mill made by the research group as the prototype,the mathematical model of "drive motor + frequency converter" transfer function is established.The mathematical model is composed of proportional link,inertia link and delay link.And then,the stability of the built transfer function is analyzed by using Nyquist criterion.(4)An adaptive neural network PID control model based on hammer mill is designed.The neural network structure and related parameters are determined,the neural network algorithm is incorporated into the S function,and the PID control model of the smashing system is designed with the help of MATLAB-Simulink graphical programming module.Finally,the simulation program is run.Through analysis,it is concluded that the accuracy,stability and robustness of the hammer mill control system based on BP neural network algorithm PID are better than conventional PID and fuzzy PID control.The research of this paper can provide theoretical support and technical reference for the optimization of working parameters of feed mill system and the research of adaptive control strategy of hammer mill.