基于混合优化算法的粮食仓储机械通风工艺优化

Optimization of Mechanical Ventilation Process for Grain Storage Based on Hybrid Optimization Algorithm

机械通风作为储粮中最常用的技术,在调节粮食的温度和水分方面起着非常重要的作用。为了缩短储粮仓中小麦机械通风的时间,降低该过程中的能耗,采用多元非线性回归法,拟合了通风口处空气温度和相对湿度、小麦初始水分和温度与通风时长的函数关系,运用粒子群-遗传混合优化算法对小麦通风时长进行了单目标优化。结果表明,降水通风过程最佳工艺参数为通风口处空气温度28℃、相对湿度25%;降温通风过程最佳工艺参数为通风口处空气温度10℃。研究结果可为小麦机械通风过程工艺参数的设置提供理论依据,具有一定的实用价值。

As the most commonly used technology in grain storage,mechanical ventilation plays a very important role in regulating the temperature and moisture of grain.In order to shorten the mechanical ventilation time of wheat in the granary and reduce the energy consumption in the process,the multiple nonlinear regression method was used to fit the functional relationship between the air temperature and relative humidity at the vent,the initial moisture and temperature of wheat and the ventilation time,and the particle swarm optimization-genetic hybrid optimization algorithm was used to optimize the ventilation time of wheat.The results show that the best technological parameters in the process of precipitation ventilation are the air temperature at the vent of 28℃and the relative humidity of 25%.The best technological parameter of the cooling process is that the air temperature at the vent is 10℃.The results provide a theoretical basis for the setting of technological parameters in mechanical ventilation process of wheat,and have certain practical value.