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A computationally efficient model for granular material piling in a container
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AI
DOI：10.1016/j.compag.2022.106692.png)
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Abstract
En 中文
This paper describes the development of a novel computationally efficient model to simulate the granular material piling process inside a container. The model computes both the granular material profile inside the container and spillage amount and location out of the container based on the cart geometry, impact location and orientation of flow of the grain transmitted into the container. The performance and utility of the grain fill model strategy is demonstrated via simulation of the grain piling process inside a grain cart during agricultural combine harvester grain unloading from the combine into a tractor-driven grain cart. The simulation demonstrates that the model can simulate both the grain profile change and spillage in real time. Experimental data collected from a benchmark system with LiDAR was used to quantify the model accuracy during grain unloading. The experimental results show that the model can achieve 0.2-m accuracy during a corn unloading process from an empty to a full grain cart.
Keywords:
Modeling
Machine vision
Harvest
Grain transfer
Piling
Journal
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Citations:
4.8W
