基于遗传算法的南瓜联合干燥工艺优化  

Process parameter optimization of pumpkin combined drying based on genetic algorithm

作　　者：吴绍锋 强华[1] 张欣 白云娇[1] 武时会 WU Shaofeng;QIANG Hua;ZHANG Xin;BAI Yunjiao;WU Shihui(Chongqing College of Humanities,Science&Technology,College of Electromechanical and Information Engineering,Chongqing 401524,China;Southwest University,College of Engineering and Technology,Chongqing 400715,China)

机构地区：[1]重庆人文科技学院机电与信息工程学院,重庆401524 [2]西南大学工程技术学院,重庆400715

出　　处：《食品与机械》2024年第7期183-191,240,共10页Food and Machinery

基　　金：重庆人文科技学院项目(编号:CRKZK2023002);重庆市教委科学技术研究重点项目(编号:KJZD-K202201801);重庆市高等教育教学改革研究项目(编号:223441)。

摘　　要：[目的]优化南瓜热风—真空联合干燥最佳工艺参数。[方法]对南瓜进行热风干燥、真空干燥及热风—真空联合干燥试验,以单位能耗、复水比及色差为评价指标,对比其干燥特性,以BP神经网络模型结合遗传算法,基于熵权结合加权评分法对南瓜热风—真空联合干燥进行多目标综合优化。[结果]同等条件下,热风干燥效率最高;当干燥温度为55℃,含水率转换点为30%时,联合干燥时间比真空干燥缩短了52.63%;真空干燥单位能耗最低;热风干燥的复水性能最差;真空干燥的色泽最好;结合BP神经网络模型的遗传算法得到最优干燥参数为热风干燥温度65℃,转换点含水率50%,真空干燥温度56.0509℃,此时单位能耗、复水比和色差值与验证实验值的平均相对误差分别为2.5%,5.53%,4.84%,均<6%。[结论]南瓜热风—真空联合干燥兼具热风干燥和真空干燥的优点,且结合BP神经网络遗传算法模型可以优化其工艺参数。[Objective]To improve the drying quality of pumpkins.[Methods]This study conducted experiments on hot air drying,vacuum drying,and combined hot air-vacuum drying,these drying characteristics were evaluated and compared based on unit energy consumption,rehydration ratio,and color difference indicators.Combining BP neural network model with genetic algorithm,combined with entropy weight and weighted scoring method,a multi-objective comprehensive optimization was carried out for the combined hot air-vacuum drying of pumpkins.[Results]Under the same conditions,the highest drying efficiency was hot air drying;And the findings revealed that at drying temperatures was 55℃,with a moisture content transition point of 30%,the combined drying method reduced the drying time by 52.63%,compared to vacuum drying.The lowest unit energy consumption was vacuum drying;The worst rehydration performance was hot air drying.The best color was vacuum drying.The optimal drying parameters determined by the genetic algorithm combined with a BP neural network model were a hot air drying temperature of 65℃,conversion point moisture content of 50%,and vacuum drying temperature of 56.0509℃.Verification experiments demonstrated that the average relative errors between the genetic algorithm optimized values and the experimental values for unit energy consumption,rehydration ratio,and color difference were 2.5%,5.53%,and 4.84%,respectively,all lower than 6%.[Conclusion]The combined hot air-vacuum drying of pumpkin integrates the advantages of both hot air drying and vacuum drying,and combined with BP neural network genetic algorithm model can optimize the process parameters for pumpkin hot air vacuum drying.

关 键 词：南瓜 联合干燥 热风干燥 真空干燥 遗传算法 熵权法 

分 类 号：TS255.3[轻工技术与工程—农产品加工及贮藏工程]