基于平衡水分模型的稻谷含水率实时监测系统

Real-time Monitoring System for Grain Moisture Content Based on Equilibrium Moisture Model

摘要:

基于静力学谷物平衡水分模型，利用无线传感器网络及嵌入式技术设计了仓储中稻谷含水率实时监测系统。通过试验验证改进Henderson、改进Chung—Pfost和改进 Owin模型及对应参数的稻谷含水率预测误差和精度，结果表明改进 Chung—Pfost模型具有准确预测的精度，且当参数A=363.06、B=0.1804、C=26.674时该模型的预测精度较高。通过测试传感器节点的传输质量，表明系统能够实现数据稳定的传输。

Abstract:

A real-time monitoring system for grain moisture content in grain storage was developed based on equilibrium moisture model, wireless sensor network and embedded technology. The error and precision which forecast by the equilibrium moisture model of modified Henderson, modified Chung—Pfost and modified Owin were verified in this experiment. The results showed that there was high precision in the modified Chung—Pfost model. Moreover, the prediction result was with higher accuracy when A was 363.06, B was 0 .1804, and C was 26.674. It was indicated that the system was able to realize stable data transmission by testing the transmission quality of sensor nod. This study presented a new method for real-time monitoring rough moisture content in grain storage, which was important significance for ensuring grain safety in storage.