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Study On Thin-layer Drying Of Carrot By Infrared And The Optimization Design Of Infrared Vegetable Drying Equipment

Posted on:2018-12-27Degree:MasterType:Thesis
Country:ChinaCandidate:D Y ShiFull Text:PDF
GTID:2321330512996010Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
Infrared drying of vegetable was a complex processes of non-steady-state heat and mass transfer,drying temperature T,thickness of slice material h,thickness of material layer ?,radiation distance L and power density g all had an impact on the drying process.Therefore,study on the influence of each factor on the drying characteristics had important significance on the optimization of drying process parameters and vegetable drying equipment.In this paper,single factor experiment and orthogonal experiment of carrot were conducted under the above 5 factors,the change rule of transverse relaxation time T2 x,peak area A2 x and peak ratio S2 x were obtained by means of LF-NMR,and the fitting analysis on mathematical model were conducted.And basing on it,the existing infrared drying equipment was optimized.The main research contents and results were as follows:?Based on comprehensive analysis of the current research status of fruit and vegetable drying at home and abroad,described the existing problems and development trends of the existing drying methods,developed a research scheme on carrot infrared thin layer drying mechanism and optimization design of infrared vegetable drying equipment.?On the basis of a large number of previous experimental studies,the single factor experiment of infrared drying of carrot was conducted to research the influence law of drying characteristics and appearance colour,and the better drying parameters were obtained.Based on this,the orthogonal experiment was conducted to study the primary and secondary factors and the significant factors that affected the drying rate.The optimal combinations of process parameters of infrared radiation drying of carrot were: drying temperature T=85?,power density g=0.60W/cm2,radiation distance L=130mm,thickness of material layer ?=15mm,thickness of slice material h=2mm.?In order to investigate the influence of different drying factors on moisture transfer during drying process,analysed the variations of transverse relaxation time T2 x,peak area A2 x and peak ratio S2 x of samples by means of LF-NMR.The research showed that,the free water,immobilized water and bound water in carrot were mutual transformed during the drying process,the fluidity and content presented different variation rules.Different phase state water showed similar change laws under the different drying factors.?In order to further explore the trend of moisture change and realize modelling in drying process.Calculated the effective moisture diffusivity(Deff)and fitted the drying mathematical models by analysing the experimental data of LF-NMR.The research showed that the range of Deff was 0.946×10-8~1.375×10-8m2/s.The Page model could be better to predict the change of moisture content MR in the infrared thin layer drying.?Based on the theoretical research above,the temperature controling and measuring device,conveyor chain plate of conveying device,arrangement mode of infrared radiating element and the drying technology parameters of the existing drying equipment were optimized,and added the material cleaning device.The preliminary test showed that the improved drying equipment could solve the problems of low accuracy of measuring temperature,obvious thermal inertia,the "cooking" phenomenon at the primary stage of drying and unreasonable power al ocation.Drying time and energy consumption had respectively reduced by 36.36% and 11.70% than ever before.The research could provide theoretical reference for the studying drying laws of agricultural products and modification and development of drying equipment.It was significant to the development of infrared drying industry.
Keywords/Search Tags:infrared radiation, thin layer drying, carrot, low field nuclear magnetic resonance, drying characteristics, equipment optimization
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