Stored Grain Volume MeasurementUsing a Low Density Point Cloud
| Autor: | Michael D. Montross, Samuel G. McNeill, Nicole K Koeninger, Josephine M. Boac, Joshua Jackson, Ronaldo G. Maghirang, Mark E. Casada, Aaron P. Turner, Sidney A. Thompson, Rumela Bhadra |
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| Rok vydání: | 2017 |
| Předmět: |
Data processing
020208 electrical & electronic engineering 010401 analytical chemistry General Engineering Point cloud Field of view 02 engineering and technology Laser 01 natural sciences Bin 0104 chemical sciences law.invention law 0202 electrical engineering electronic engineering information engineering Compressibility Metre Environmental science Remote sensing Volume (compression) |
| Zdroj: | Applied Engineering in Agriculture. 33:105-112 |
| ISSN: | 1943-7838 0883-8542 |
| DOI: | 10.13031/aea.11870 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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