Study On Low Energy Consumption Control Strategy In Molecular Distillation Process

With the increasing awareness of food and health,the demand for green food is becoming higher and higher.The return to nature has prompted the rapid development of molecular distillation technology,making this pure physical separation technology more and more popular.This paper aims at the problem of nonlinear,large time delay,process,complex distillation mechanism and high energy consumption in the process of molecular distillation.The experimental platform of three stage molecular distillation unit,which can be adjusted by evaporation temperature,speed of scraping film and vacuum degree,is studied.The crude oil of Schisandra with supercritical extraction is used as the experimental raw material.The purification of terpenes from Schisandra chinensis was carried out.In order to reduce the energy consumption of the system,three aspects of distillation process,structure and control method are studied in this paper.Negative pressure low temperature evaporation process is used to carry out low temperature evaporation under high vacuum.The structure of the wall of the distillation equipment is improved,and the retention time of liquid is prolonged by adding a micro convex reticulate circle,and the distillation is improved.The structure of the cooling system is optimized,the coupling structure of the constant temperature water loop and the cooling water loop is constructed,and the cooling energy and waste heat of the refrigerator are used to preheat the material,and the energy consumption can be reduced effectively.In view of the 3 technological parameters of the distillation temperature,vacuum degree and the rotational speed of the scraper,the experiment first adopted the single factor experiment method which fixed the other technological parameters,and obtained the influence data of the process parameters on the product purity and yield,and carried out a comprehensive analysis.The data of the molecular distillation process parameters and the product purity obtained by the experiment were analyzed.The function model of molecular distillation process parameters and product purity and product yield is established by using the two response surface regression modeling principle,and a system process parameter optimization model based on multi-objective genetic algorithm is established.Through the combination of numerical simulation and experiment,the model is solved with the energy consumption as the constraint condition,the purity and yield are solved as the optimizationtarget model.The genetic algorithm is used to optimize the parameters,and the "good point set" is introduced to select the population,and the optimization efficiency of the genetic algorithm is improved.The optimal parameters can be obtained more quickly and accurately to achieve the effect of reducing energy consumption.The optimized multi-objective particle swarm optimization was used to optimize the two target optimization model of the molecular distillation.The optimum parameters of the process parameters under the minimum energy consumption were 300r/min,the vacuum degree30 Pa of the distillation process and the evaporation temperature of 120.The fuzzy PID algorithm is applied to realize the intelligent control of evaporator temperature in molecular distillation.Due to the characteristics of large temperature delay,Smith predictive control is added to the control process.The input parameters of the controller are the temperature deviation and the variation rate of the deviation,and then the fuzzy PID control table is obtained by fuzzy reasoning.Thus the three control parameters of PID are changed in real time to obtain the ideal control quality,and the stable temperature is controlled at the steady state at 120 C,and the large time delay problem of temperature control is solved.It has strong robustness and anti-jamming performance.