Study On Commutating Ventilation In Alfalfa Solar Drying And Forecasting Model

The traditional process of alfalfa drying is poor of uniformity and Degree of automation.The study is based on the test bench for solar drying alfalfa test. Analyzing the problems in the alfalfa drying to improve the drying process of alfalfa. Acquired the temperature, relative humidity of the alfalfa in the drying oven and the temperature, relative humidity outside of the drying oven. Plotting graphs and three-dimensional field distribution were been used to study and discussion that based on data that we got previously, the results shows that, during the process of deep-seated drying, the inverting ventilative drying craft is able to improve the drying uniformity of same and different levels’alfalfa in drying box effectively. It has important practical significance in enhancing drying rate and quality of alfalfa.Prediction model of alfalfa drying rate which aimed to different levels within the oven and the overall alfalfa was been built by Elman neural network with data from drying tests, since the accuracy of the prediction model, it can provide the basis for craft optimization match.