Abstract

A dynamic grain flow model describes how the grain flow at the end of the threshing process reacts to feedrate variations during harvest. These input flow variations have different origins as there are variations in travel speed, cutting width and locally variable grain yield. In this study, an analysis of the model is performed and a specific application in the domain of precision farming is illustrated.A closer look at the construction of the analytical grain flow model reveals some complicated dynamics in the system and an internal return loop with a significant time delay. Especially, the latter property makes it difficult to simplify the model into a linear transfer function, an interesting form for further applications. Due to a specific property of grain spreading in the return flow, it is possible to compensate for the variations in the return flow fraction. The grain smoothing effect of the combine harvester for 0% return flow was approximated by a fourth-order linear transfer function.Some producers of combine harvesters already possess a commercial product for online grain yield measurement. These sensors are typically mounted at the end of the threshing process since this is the only place where a flow of clean grain is present. Nevertheless, this position has also a drawback. Grain flow signals, measured at the end of the threshing process contain unconditionally the influence of disturbing machine dynamics. In practice, this means that feedrate variations and subsequently estimated yield variations, are smoothed reducing the economic interest of the resultant yield maps. The inverse simplified linear transfer function makes it possible to reduce these latter errors and to improve immediately the results of further site-specific grain yield analysis.

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