佛手瓜的微波真空干燥及其神经网络模拟的研究

考察了佛手瓜真空微波干燥过程中,干燥时间、微波功率、真空度、转速、厚度等因素对干燥率的影响,用BP神经网络建立了干燥率与这些因素的关系模型,并应用MATLAB神经网络工具箱实现对该模型参数的训练和系统模拟。结果表明,不论微波真空干燥因素如何变化,只要用一定的实验数据对模型进行训练,然后对拟采用的干燥条件进行仿真,均可得到较为可靠的目标参数.

Study on microwave vacuum drying of chayote and its simulation based on neural network

In this paper, the effect of dry time, power, rotate speed, vacuum degree and thickness on drying rate was studied in the drying of chayote. The model of the relationship between the effect of microwave vacuum drying of chayote and these dry factors was established by the BP neural networks method. The relation model was trained, as well as the system simulation was implemented by MATLAB. However the factors were changed, the satisfied quality targets would be achieved as long as the model with certain experimental data was trained before the system simulation was on the adopted parameters of drying.