Optimization Of Dryer Corner Box Structure And Its Whole Machine Control System Research

The 14th Five-Year plan consolidates the foundation of food production capacity,to ensure the security of the food supply.Strengthen the research and development of large and medium-sized,intelligent,composite agricultural machinery applications,etc.,emphasizing the focus on food and the determination to ensure food security.This thesis takes the circulating dryer as the research object,the drying structure and control system of the dryer are optimized and designed,including three aspects: First,the drying structure of the dryer is optimized and designed,the problems of uneven drying and dead angle of grain are improved,the quality of the dried grain is improved and the energy consumption is reduced;Second,the variable temperature and variable speed adaptive control system of the dryer is established to improve the control accuracy and drying rate of the control system and reduce energy consumption;Third,the optimal moisture content prediction model is estabished and combined with fuzzy PID to further improve the control accuracy of the dryer control system and the quality of the grain after drying.Based on the above ideas,the main research work of this thesis is shown as follows:(1)Numerical simulation of the drying section angular box.Based on the real object as the prototype,the drying section of the dryer was modeled in Solid Works software,and the structure of the model was optimized and designed.The model is analyzed by numerical simulation using Computational Fluid Dynamics(CFD)technology.Based on the obtained pressure,temperature,and air velocity unevenness coefficients,the optimal parameters and optimal structure of the dryer corner box structure are investigated to improve the drying effect of the drying section of the dryer,and finally,the correctness of the simulation is verified by comparing the test with the simulation.(2)The dryer variable temperature variable speed adaptive control system was designed.The overall framework of the control system is built,the hardware modules required for the control system are determined,the circuit design is carried out for each module,and the schematic drawing is carried out using Altium Designer(AD)software,and soldered into a PCB board According to the schematic drawing of the hardware,the design is based on STM32 microcontroller as the core,and the program is written in Keil software to control each module,and finally Realize the variable temperature and variable speed control of the system,and finally debug the whole control system to verify the accuracy and reliability of the control system.(3)Establishing an optimal moisture content prediction model.The moisture content,drying temperature,airspeed,and initial moisture content data were collected at different time periods when the grain was dried in the dryer,and the moisture content prediction models of the BP neural network and Support Vector Machine(SVM)were established based on the collected data.The prediction models were optimized by Genetic Algorithm(GA)and Sparrow Search Algorithm(SSA),and six different prediction models were obtained.Each model was double-analyzed based on different evaluation criteria,prediction results,and errors,and the optimal water content prediction model was obtained.(4)Joint simulation of water content prediction model and fuzzy PID control.According to the fuzzy PID principle,the simulation of the fuzzy PID control system is built by MATLAB software and combined with the optimal water content prediction model for joint simulation,and the actual water content is corrected in real-time.A comparative analysis of the system by adding PID and fuzzy PID control to the original model finally leads to the optimal control strategy.