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基于多目标遗传算法的山药真空干燥工艺优化

Optimization of Vacuum Drying Technology of Yam Based on Multi-Objective Genetic Algorithm

  • 摘要: 为了得到山药切片真空干燥的最优工艺参数,以平均干燥速率Y1、单位能耗Y2、复水比Y3和白度指数Y4为试验指标,以干燥温度T、压强V和切片厚度L为影响因素进行进行Box-Behnken响应面优化试验,通过多元非线性回归分析建立各指标的数学模型,最后分别使用加权评分法和遗传算法进行多目标优化。结果表明:多目标遗传算法优化结果更合理,得到的山药切片真空干燥最优工艺参数为:干燥温度63.76℃、压强0.0532 MPa和切片厚度2.46 mm,所对应的指标值为:平均干燥速率0.00897 g/(g·min)、单位能耗14.205 kW·h/kg、复水比2.078和白度指数81.220。

     

    Abstract: In order to obtain the optimal process parameters of vacuum drying of yam slices, Box-Behnken response surface optimization test was carried out with average drying rate Y1, unit energy consumption Y2, rehydration ratio Y3 and whiteness index Y4 as the test indexes, and drying temperature T, pressure V and slice thickness L as the influencing factors. The mathematical model of each index was established by multiple nonlinear regression analysis. Finally, the weighted scoring method and genetic algorithm were used for multi-objective optimization. The results show that the optimization result of multi-objective genetic algorithm is more reasonable. The optimum vacuum drying parameters are as follows: drying temperature 63.76℃, pressure 0.0532 MPa and slice thickness 2.46 mm.The corresponding index values are average drying rate 0.00897 g/(g·min), unit energy consumption 14.205 kW·h/kg, rehydration ratio 2.078 and whiteness index 81.220.

     

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