Study On Heat And Mass Transfer Model And Drying Efficiency Promotion Of High Frequency Vacuum Drying Of Pinus Sylvestris Var.Mongolica Litv.

Due to the natural,low-carbon,environmental protection and adjustment advantages of wood structure architecture,it is favored by people and the demand is increasing year by year.The demand for the large section structural timber used in wood structure and the large section high-quality sawn timber used in planing and dividing wood floor increases correspondingly.Therefore,it is of great significance to study the high quality,fast and energy saving drying technology of the large section wood.High frequency vacuum drying technology combines the advantages of high frequency drying and negative pressure drying.It is an ideal drying method for precious tree species,wood crafts and large section wood with good permeability.However,the uniformity of temperature distribution is poor during high frequency heating of wood.Improper operation would increase the temperature difference between the wood surface and core and seriously affect the drying quality of wood.In the high frequency vacuum drying process,moisture content and strain of wood cannot be detected online in real time,which results in the failure to accurately grasp the drying quality.In addition,it is necessary to find an appropriate way to pretreat the test material to improve its permeability and dimensional stability,so as to give full play to the advantages of high frequency vacuum drying and improve the drying efficiency.In view of this,the paper used section 120mm×120mm Pinus sylvestnis var.mongolica Litv.timber of suitable for wooden structure building columns as the test materials.Aiming at solving the above problems,the heat and mass transfer model in high frequency vacuum drying process was established,solved and verified.On this basis,the improvement measures of high frequency heating uniformity were discussed to improve the high frequency heating efficiency,and the change prediction of wood moisture content distribution and drying strain detection were realized in the high frequency vacuum drying process,so as to optimize and implement the drying process reliably and improve the drying efficiency.It is not only of great significance to optimize the drying process and improve the drying quality,but also can provide the basis for the implementation of precise automatic control of the drying process.The main research contents and achievements of this paper are as follows:(1)Detection of wood thermal and dielectric properties and analysis of the influence of moisture content and temperature on it.The effects of moisture content,temperature and texture direction on the thermal conductivity and dielectric properties of mongolian pine were analyzed.The results showed that the thermal conductivity increased with the increase of temperature and moisture content.The dielectric constant increased with the increase of moisture content,in which the relation was exponential at the fiber saturation point and linear at the fiber saturation point.Regression equations of thermal conductivity and dielectric constant with respect to moisture content and temperature with higher accuracy were obtained.The correlation coefficient between the calculated value and the experimental value of thermal conductivity was 93%;the correlation coefficient between the calculated value and the experimental value of each regression equation of the dielectric constant were 99.1%,99.5%,and 99.8%,which were in good agreement.(2)Study on heat transfer model and heating uniformity improvement of wood during high frequency heating.The finite element method was used to establish the wood high frequency heating model.On this basis,the parameters such as plate spacing,area of the power supply plate,dielectric constant,heating time,length and width of stack were changed in the model to solve and analyze the influence of each parameter on the uniformity of high frequency heating.Finally,an improved scheme of wood high frequency heating uniformity was proposed and verified.The results showed that:? The range of the root mean square error(RMSE)of the simulated and measured temperature was 0.0074-0.074;Comparing the analysis of the error between the simulated and measured heating rates,the accuracy during the early and later stages of drying was high,with an error between 2%and 4%,and the error near the fiber saturation point was 21.8%;The overall model had good accuracy and could well predict the change of wood temperature distribution during high frequency heating.? In the thickness direction,the stack temperature distribution showed that the center layer temperature(62?-70?)was the highest,and the upper and lower layer temperatures(50?-56?,50?-55?)were the lowest;in the length direction,the core temperature(53.5?-65.4?)was lower than the temperature at both ends(50.7?-68.6?);When stacking wood,placed a layer of dried sheet of a certain thickness between the stack and the ground electrode plate,and wood,dry sheet,plate between no gap;When the area of the electrode plate was S5(500mm×240mm)and was same with the horizontal cross-sectional area of the stack,the heating uniformity was the best;The high-frequency heating time was controlled within 5-15min according to actual needs.? After the improvement,the electromagnetic field distribution between the upper and lower electrode plates was more uniform,and the temperature difference among the center position and length,width,thickness direction of the sample was reduced by 7.6?,1.7?,and 3.4?,respectively.The temperature distribution was more uniform,the heating effect was more ideal.(3)Study on the mass transfer model of wood in the process of high frequency vacuum drying.The study was based on BP(Back Propagation)neural network algorithm to predict the change of wood moisture content during the high frequency vacuum drying.The data of real-time online measurement were used to construct the model,the drying time,position of measuring point,and internal temperature and steam pressure of wood as inputs of BP neural network model.The results indicated that the model structure was 4-6-1(input layer-hidden layer-output layer)and the decision coefficient R2 and Mean squared error(Mse)of the training sample were 0.974 and 0.07355,respectively.It indicated that the neural network model had superb generalization ability.Compared with the experimental measurements,the predicted values conformed to the variation law and size of experimental values,and the error was about 2%and the MC prediction error of measurement points along thickness direction was within 2%.Hence,the BP neural network model could successfully simulate and predict the change of wood MC in the high frequency drying process.(4)Study on strain distribution and variation of wood during high frequency vacuum drying.Taking mongolian pine as the research object,the strain distribution and changes in the drying process of wood were detected based on DIC technology.The results showed the following:Compared with traditional strain measurement methods,the measurement accuracy of DIC technology can be improved by 1.7%-5.3%,which can be used for on-line strain monitoring during wood drying.When dried below the wood fiber saturation point,the difference of the radial and tangential shrinkage ratio increased gradually.In the later stage of drying,the tangential shrinkage was approximately 2 times of the radial shrinkage.Analysis of tangential and radial strain distribution:The radial strain distribution was more dispersed than that of the tangential due to the difference of the early and late wood.The radial strain distribution was compression strain at both ends and tensile strain at the center.The tangential strain distribution was tensile strain on the left and compressive strain on the right.(5)Effect of heat and humidity pretreatment on high frequency vacuum drying efficiency of wood.Before the high frequency vacuum drying,the saturated wet air,saturated steam at atmospheric pressure and high-temperature setting were carried out on section 120mm×120mm mongolian pine respectively,and the influence of the pretreatment on the moisture content,drying rate,drying cracking and drying strain were discussed.The results showed that:?Saturated wet air and atmospheric pressure saturated steam pretreatment could reduce the initial moisture content of the test material by 2.6%-6%;The moisture content distribution was more uniform,the maximum difference of moisture content of wood after drying was 2%,and the pretreatment wood was less than 1%;The drying rates was improved,untreated,saturated wet air and atmospheric pressure saturated steam pretreated wood were 0.268%/h,0.333%/h and 0.398%/h,respectively.The method could reduce the drying strain and the cracking of the test material,but it could not suppress the cracking completely.? High temperature setting pretreatment could inhibit the surface cracking under the appropriate process conditions,and effectively improve the drying quality of mongolian pine;By comparing and analyzing the drying quality of different pretreatment processes,it was found that the optimal pre-treatment process was:Saturated wet air at 90? was treated for 12h,then dry bulb temperature at 120?and wet bulb temperature at 90? were treated for 8h.