| The research of forage drying equipment plays an important role in the development of animal husbandry.A complete drying equipment is mainly composed of heating system,drying chamber and drying material rack.As an important part of drying equipment,the structure of drying material rack not only affects the quality of finished forage,but also has a decisive influence on the degree of manual participation in the drying process and the yield of forage.In this thesis,TGS-2 bales of alfalfa solar-heat pump combined drying device is taken as the research object.In view of the problems of uneven drying,low efficiency,poor controllability and compatibility of forward and backward channels between existing equipment and forage processing in the process of drying operation,the structure and control strategies of drying material rack are improved.The concept of adaptive control is introduced into the system control process.In order to improve the detection and automatic control level of solar-heat pump combined drying device,the main research contents of this thesis are as follows :(1)Aiming at the problems of the TGS-2 bales of alfalfa solar-heat pump drying test bench,such as large differences in drying rate,poor uniformity and low production efficiency of grass materials at different positions,it is proposed to change the static drying material rack into a conveyor belt multi-layer dynamic conveying device.(2)To obtain the control parameters of the dynamic conveying device,a hot air convection drying experiment was conducted on alfalfa.Under the same drying medium conditions,the correlation analysis of drying influencing factors was carried out,and the primary and secondary factors affecting the drying rate were obtained : hot air velocity >hot air temperature > alfalfa thickness.The relationship between the state of drying medium and the moisture content of alfalfa was studied under different drying medium conditions.It was determined that the humidity factor of drying medium on the surface of alfalfa could be used to predict the moisture content of alfalfa.The mathematical model of moisture content(W)and drying time(t)of alfalfa was established by multivariate nonlinear regression analysis.A prediction model based on BP neural network was established to realize the online prediction of alfalfa moisture content during drying operation through medium humidity factors.(3)On the basis of experimental research,the moisture content predicted by BP neural network combined with multiple nonlinear regression model was determined,and the drying time of alfalfa moisture content drying to the target moisture content in the drying process was inversely calculated.According to the length and drying time of the conveyor belt,the frequency conversion motor speed control was used to realize the strategy of controlling the moisture content of alfalfa drying to the outlet of the dynamic conveying device.Based on the control strategy,the S7-200 PLC was used as the control unit,and the MCGS touch screen was used as the host computer.Through the multi-speed function of the inverter,the control system of the variable frequency motor speed regulation was realized,and the monitoring and control of the drying process through the host computer was realized.(4)Based on the TGS-2 bales of alfalfa solar-heat pump drying device,the designed control system was verified.The results showed that the control system had high control accuracy for alfalfa moisture content,which effectively reduced the degree of manual participation and improved the automation level of the drying process. |
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