Construction of Relationship Model between Moisture Content and Dielectric Constant of Apple
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摘要:
介电常数与含水率有较高的相关性,可通过测量农产品的介电特性参数预测其干燥过程含水率,高压脉冲电场可有效加快干燥过程,但介电常数和含水率在此过程中的影响机理尚待进一步研究。为解决高压脉冲电场作用下果蔬介电常数与含水率之间关系的微观解释不明确问题,以苹果为研究对象,建立有效的苹果含水率与介电常数关系模型,三维模拟其内部电场参数,使用蒙特卡罗法对高压脉冲电场下苹果的介电特性进行理论模拟计算,把苹果内部宏观和微观介质作为集总参数来等效替代其内部整体结构。试验结果表明,当修正系数8.96时,控制苹果相对水含率从88%逐步下降到18%,介电常数计算值与实测值间相对误差稳定在10%以内。研究为脉冲电场处理果蔬加工提供理论依据。
Abstract:There is a high correlation between dielectric constant and moisture content, and drying process moisture content of agricultural products can be predicted by measuring their dielectric characteristic parameters.High voltage pulse electric fields can effectively accelerate drying process, but influence mechanism of dielectric constant and moisture content in this process still needs further research.In order to solve problem of unclear micro explanation of relationship between dielectric constant and moisture content of fruits and vegetables, taking apples as research object, an effective model was established for relationship between moisture content and dielectric constant of apples, their internal electric field parameters in three dimensions was simulated, Monte Carlo method was used to theoretically simulate and calculate dielectric properties of apples under high-voltage pulse electric fields, and macro and micro media inside apples was treated as lumped parameters to effectively replace their overall internal structure.Experimental results showed that when correction coefficient was 8.96, relative water content of apple was gradually reduced from 88% to 18%, and relative error between calculated and measured values of dielectric constant was stable within 10%.The study could provide a theoretical basis for processing of fruits and vegetables using pulsed electric fields.
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表 1 两相不同体积比和相对含水量下苹果介电常数及误差
Table 1. Dielectric constant and errors of apples at different volume fraction and relative moisture content
两相体积比(V1/V2) 相对含
水量/%介电常数
实测值介电常数
计算值宏观介
电常数相对误差/% 0.12/0.88 88 6.0 5.644 50.572 −6.778 0.19/0.81 81 4.8 5.176 46.377 6.850 0.30/0.70 70 3.1 3.426 30.701 9.123 0.39/0.61 61 3.2 3.255 29.166 1.254 0.42/0.58 58 3.0 3.200 28.678 5.851 0.59/0.41 41 2.5 2.776 24.877 9.555 0.67/0.33 33 3.0 2.760 24.735 −9.157 0.79/0.21 21 2.2 2.321 20.799 4.803 0.82/0.18 18 2.0 2.068 18.526 2.839 -
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