Application of Multi-sensor Information Fusion on Monitoring and Controlling System of Stored-grain Condition

Abstract

To guarantee the grain’s safe storage, it’s necessary to strictly control the stored-grain’s internal and external influence factors such as temperature, moisture, humidity and pests. The application of information fusion techniques on monitoring and controlling system of stored-grain condition is a useful consideration. In this paper, a new method based on multi-parameter and two stage information fusion techniques is proposed. In the process of fusion, the BP neural network technique and D-S evidence theory are mainly applied. This method,characterized by sufficiently utilizing the effective detected condition data, optimizing homogeneous data and considering the complementation of the different data source, improves the whole stored-grain condition’s monitoring and control system’s reliability.