Research On Back Pressure Control System Of Injection Molding Machine Based On Self-learning Optimization PID Algorithm

At present,the back pressure control methods of hydraulic injection molding machine in the pre molding stage mainly include direct control with proportional relief valve as the main control valve and indirect control with proportional servo valve as the main control valve.With the increasing demand for energy conservation in manufacturing industry,the research on low back pressure control technology has become a breakthrough for injection molding machine enterprises to achieve energy conservation.The current proportional relief valve and proportional servo valve used to control the back pressure are difficult to achieve low pressure control of the injection molding machine back pressure because of their structural limitations.In order to solve the shortcomings and drawbacks of the current control scheme,this paper proposes a new scheme for low back pressure control,and selects proportional directional valve as the back pressure main control valve.Taking the proportional directional valve produced by a company as the research object,the dual-channel connection method is adopted to increase the flow,and the self-learning algorithm is used to optimize the PID control to improve the control accuracy and achieve the purpose of low back pressure control.Firstly,the relevant data of back pressure control at home and abroad are searched,and the theoretical feasibility of the new scheme is verified by combining theoretical analysis and simulation modeling.Then,the control effect of different algorithms is compared,and the best control scheme is obtained based on the evaluation criteria of overshoot size and reaction time.Design the hardware controller according to the control scheme and the algorithm used;Finally,test bench experiments are carried out to verify the feasibility of the control scheme.These include:1 A lot of relevant information was found for the back pressure control scheme,theoretical discussion was conducted with the R&D engineers,and joint simulation was carried out through MATLAB and AMEsim software:corresponding mathematical models were built for three different algorithms in the MATLAB software simulink module,and in AMEsim software,the reverse force borne by the screw in the pre molding stage was simulated by the hydraulic motor,hydraulic pump,and mechanical transmission structure,The actual one-way hydraulic piston is replaced by the two-way hydraulic piston.2 The simulation results of conventional PID algorithm,BP neural network PID algorithm and self-learning optimization PID algorithm are compared and analyzed by taking the overshoot value and response time of proportional directional valve P port pressure fluctuation as the evaluation criteria,which lays a foundation for subsequent work.3 Then the hardware control board is designed according to the simulation results and the actual working conditions,and the component models are compared and selected,the hardware circuit diagram is drawn,PCB layout,welding,debugging,and optimization of the hardware controller are carried out.4 Generate the self-learning optimization PID algorithm code and program the control board control chip,connect the control board and the proportional directional valve,and connect the proportional directional valve to the test bench for experimental verification.Experimental results show that the control scheme proposed in this paper can achieve low back pressure control,achieve the control accuracy required under actual working conditions,and verify the feasibility of the control scheme...