This technical note presents the development of a new apparatus and data processing method to accurately estimate the volume of stored grain in a bin. Specifically, it was developed to account for the variability in surface topography that can occur in large diameter bins when partially unloaded. This was accomplished using a laser distance meter to create a low density point cloud, from which a surface was interpolated using ArcMap geoprocessing tools. The manually controlled and portable system was designed to hold the laser distance meter and provided a common reference point. The data from the laser distance meter was transmitted to a tablet PC via Bluetooth. Measurement of an empty hopper bottom bin (4.6 m in diameter and 6.5 m tall) demonstrated that the system was able to measure a known volume within 0.02%, and repeated measures of an empty flat bottom bin (1.8 m in diameter, and 5.7 m tall) were within 0.29% of the known volume. Two applications are presented which highlight the system‘s ability to capture complex surfaces, as well as limitations that result from fill scenarios where the field of view was limited.
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The research was supported by the USDA (CRIS No. 5430-43440-007-08R and RMA Agreement No. 09-IA0831-0096). This work is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch-Multistate under 1002344.
This is publication No. 15-05-073 of the Kentucky Agricultural Experiment Station and is published with the approval of the Director.
Turner, Aaron P.; Jackson, Joshua J.; Koeninger, Nicole K.; McNeill, Samuel G.; Montross, Michael D.; Casada, Mark E.; Boac, Josephine M.; Bhadra, Rumela; Maghirang, Ronaldo G.; and Thompson, Sidney A., "Stored Grain Volume Measurement Using a Low Density Point Cloud" (2017). Biosystems and Agricultural Engineering Faculty Publications. 73.