Research On Quality Characteristics And Windows-control Method Of Variable Temperature And Humidity Grain Drying Process By Coupling Factors

As an important link in the agricultural production process,grain drying is a comprehensive technology covering many disciplines,including heat and mass transfer,biophysics,mechanics,computer science and so on.Admittedly,exploring a more reasonable drying process and control method has great significance for the upgrading of key working equipment in grain industry so as to guarantee the food safety.In view of the single factor control's limitation and the development demands of multi-factor intelligent control in grain drying technology and equipment,the author adopted the self-developed multi-parameter controllable drying test system in this dissertation to research the influence models and laws of eight types of coupling factors on grain drying,variable-parameter drying properties and quality characteristics,which revealed the correlation between the coupling factors and the grain characteristic index,thus selecting the accumulation of grain absolute water potential as the ideal coupling factor in the drying process to improve the dual-drive interactive window-control method of continuous grain drier.And then this method had been applied to the continuous drying operation of rice,which achieved good control effect.The specific research contents were as follows:1.Analysis and Selection of Coupling Factors in the Grain Drying ProcessOn the basis of the characteristics of grain drying process and our research group's exploration on the concepts and models of absolute water potential and equivalent accumulated temperature,the author selected eight coupling factors,including equivalent accumulated temperature of grain(EATG),equivalent accumulated humidity of grain(EAHG),sum of grain absolute water potential(SGAWP),sum of air absolute water potential(SAAWP),the deviation of SGAWP subtracting SAAWP,accumulation of grain absolute water potential(AGAWP),accumulation of air absolute water potential(AAAWP),the deviation of AGAWP subtracting AAAWP,to study the laws and characteristics of grain drying and variable-parameter drying,and finally defined eight coupling factors'calculation formulas.2.Study on the Correlation between Coupling Factors and Maize Characteristic Index,and the Technical Optimization of Drying ProcessThe ideal coupling factors of the drying process control should be selected to optimize the drying process.Taking corn as the test sample,we carried out the two-factor five-level thin layer drying full factorial experiment by using the self-developed multi-parameter controllable drying test system,selecting temperature gradient change of hot air(x₁)and absolute humidity gradient change(x₂)as test variables with two drying characteristic indexes and thirteen quality characteristic indexes as response indexes to investigate the influence trend of test variables on response indexes.Variance analysis of 8 drying system coupling factors and corn response indexes,sort it according to the confidence level.Among them,the correlation between"accumulation of grain absolute water potential(AGAWP)"and the maize response index was the most significant one,with an R²mean score of 0.6736.Therefore,the AGAWP was selected as the ideal coupling factor for the drying process control.The quadratic regression model and response surface of the response index on test variables were established through using the software ORIGIN8.0 to find the optimal drying process corresponding to each response index.For the non-commensurability and contradictoriness of the optimal drying process under each corresponding response index,it could not be simply added or subtracted.Hence,we continued to use the MATLAB software to integrate all the response indexes into a comprehensive characteristic index combined with the concept of deviation quantity,and then applied the genetic algorithm to keeping optimization.It was concluded that the comprehensive characteristics of maize were the best when adopting the gradually warming and gradually dehumidifying drying process(i.e.,x₁=2.17?,x₂=-3.03g/m³),which realized the cooperative regulation of drying energy consumption and quality.3.Study on the Correlation between Coupling Factors and Rice Characteristic Index,and the Technical Optimization of Drying ProcessIn order to verify the generality of the conclusion of maize drying test,rice was selected as the sample for reproducibility verification.We carried out the two-factor five-level thin layer drying full factorial experiment by using the self-developed multi-parameter controllable drying test system,selecting temperature gradient change of hot air(x₁)and absolute humidity gradient change(x₂)as test variables with two drying characteristic indexes and fourteen quality characteristic indexes as response indexes to investigate the influence trend of test variables on response indexes.In the same way,variance analysis of 8drying system coupling factors and corn response indexes,sort it according to the confidence level.Among them,the correlation between AGAWP and the rice response index was the most significant one,with an R²mean score of 0.6809.Therefore,the AGAWP was selected as the ideal coupling factor for the drying process control.The results of drying process optimization showed that the comprehensive characteristics of rice were the best when adopting the gradually warming and gradually dehumidifying drying process(i.e.,x₁=2.57?,x₂=-21.04%).The conclusion of rice test was basically consistent with that of maize test.4.Improvement of Continuous Grain Drying Control Method Based on the Ideal Coupling FactorThe ideal coupling factor was applied to the interactive window-control method of grain continuous drying that was previously studied by our research group,the dual-drive interactive window-control method of grain continuous drying was designed,to improve the stability of drying process control and grain drying quality.This method included three parts:window selection based on mechanism driven,window adjustment based on data driven and window adaptation.Firstly,the author selected AGAWP as the control window and grain export moisture as the actualization window to form a pair of interactive windows.And then,according to the two-factor five-level full factorial experiment data of rice,the moisture ratio curve changing with AGAWP was used to fit eight common exponential models.In this dissertation,the author chose to establish the mechanism driving model based on Weibull equation under the guidance of Akaike Information Criterion(AIC).Finally,the mechanism model was adopted to determine the size of the initial window area.Furthermore,according to the comparison and analysis of real-time data and historical data,the adjustment of the window area and the adaptive function of the window length-width ratio were realized by adjusting the idle time of the closed fan,so as to optimize the window shape.5.Experimental Test on the Improved Method of Dual-Drive Interactive Window Control for Continuous Grain DryingThe continuous rice drying operations based on this improved method of dual-drive interactive window-control proved that this method had an ideal effect in controlling stability and improving the grain drying quality.In this dissertation,three groups of continuous rice drying experiments were carried out using a continuous grain drying machine independently developed by the research team based on the optimization results of the drying process in the two-factor five-level full factorial experiment of rice.The three groups of continuous rice drying experiments were the constant temperature drying group based on the improved method(Experiment 1),the heating drying group based on the improved method(Experiment 2),and the constant temperature drying group based on the original method(Experiment 3).By comparing the quality changes and the microstructures of the rice before and after drying,it was concluded that the improved method achieved better rice drying quality than the original method,and the quality of the rice produced by the heating drying process was better than that produced by the constant temperature drying process.After calculating the Pearson correlation coefficient between the target outlet moisture change curve and the outlet moisture change curve after the system became stable,the following result was obtained:the Pearson correlation coefficients of the three groups of experiments were 0.9074,0.9060,0.8255,respectively,which indicated that the control stability of the improved method was better than the original method,and the outlet moisture stability produced by the constant temperature drying process was better that produced by the heating drying process.This amply proved that the improved method of dual-drive interactive window-control had an ideal effect in improving the accuracy of grain outlet moisture control and the grain drying quality.Therefore,this control method can be applied in practice to realize automatic control for the drying process,and has eventually achieved the research purpose of this dissertation.