基于改进粒子群算法的大豆微波真空干燥工艺优化

为了发现大豆的微波真空干燥的最佳工艺条件，测试了不同的单次干燥时间、缓苏时长、缓苏次数下大豆干燥后含水率与爆腰率，提出了一种基于改进粒子群算法的参数寻优方法，新建次空间，主次空间交换精英个体，借助多元回归数学模型对实验参数进行粒子寻优。结果表明：简单地增加缓苏时长与缓苏次数并不一定利于提高大豆干燥效果，不同缓苏条件相互影响，大豆在单次干燥35min、缓苏50min、缓苏3次时干燥效率最高；在单次干燥35min、缓苏40min、缓苏3次时爆腰率最小。实验证实了采用改进粒子群算法优化参数干燥后大豆的爆腰率和含水率均低于正交实验优化的结果。研究结果对于提高大豆干燥效率和品质具有一定意义，并为微波真空干燥产业化应用及大豆深加工提供参考。

Optimization of soybean microwave vacuum drying process based on improved particle swarm algorithm

In order to find the best process conditions for microwave vacuum drying of soybeans, the moisture content and fissure rate of soybeans after drying were tested under different single drying time, tempering time and tempering times. A parameter optimization method based on improved particle swarm optimization algorithm was proposed. Secondary space was built. Primary and secondary space exchanged elite individuals. With the help of multiple regression mathematical model, the particle optimization of experimental parameters was carried out. The result shows that simply increasing the time and times of tempering does not necessarily improve the drying effect of soybean, and different tempering conditions affect each other. The drying efficiency of soybean was the highest when the single drying time was 35 min, the tempering time was 50 min and the tempering times was 3. The fissure ratio was the lowest when the drying time was 35 min, the tempering time was 40 min and the tempering times was 3. Experimental results show that the fissure ratio and moisture content of dried soybean optimized by improved particle swarm algorithm are lower than those optimized by orthogonal experiment. The research results have certain significance for improving the drying efficiency and quality of soybean, and provide reference for industrial application of microwave vacuum drying and deep processing of soybean.