Grain Analysis Method and Model Research of High and Big One-Storey Granaries in North Cold Regions

Abstract

High and big one-storey granaries are the large-scale grain storage facilities generally adopted in our country. Mass data are obtained through the grain monitoring system equipped for a great number of high and big one-storey granaries, but they are only explored and utilized by resorting to the working experience of management personnel, without any scientific instruction on the operating management of granaries. With No. 49 silo of Qinjia Granary as the example, and through the data classification methods of four-layer one-shell and seven-core one shell, the paper analyzes grain data of high and big one-storey granaries in northeast cold regions of our country, and establishes the time series prediction model. The findings indicate that the two data classification methods can efficiently simplify the analysis process, and display spatial-temporal variation rules of grain; the relevancy between grain temperature data and ambient temperature data of high and big one-storey granaries is weakened gradually from top layer, middle layer, and lower layer to bottom layer. In reality, grain risk degree can be judged according to grain data of the middle layer, such as range, change rate, etc. Grain temperature data of high and big one-storey granaries conform to the sinusoidal variation model in terms of layer and core, and there are the differences in range and phase angle.