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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Publications at this Location » Publication #328610
Research Project: Impacting Quality through Preservation, Enhancement, and Measurement of Grain and Plant Traits

Location: Stored Product Insect and Engineering Research

Title: Technical Note: Stored grain volume measurement using a low density point cloud

Author
item TURNER, AARON - University Of Kentucky
item JACKSON, JOSHUA - University Of Kentucky
item KOENINGER, NICOLE - University Of Kentucky
item MCNEILL, SAMUEL - University Of Kentucky
item MONTROSS, MICHAEL - University Of Kentucky
item Casada, Mark
item BOAC, JOSEPHINE - Kansas State University
item BHADRA, RUMELA - Kansas State University
item MAGHIRANG, RONALDO - Kansas State University
item THOMPSON, SIDNEY - University Of Georgia

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/2016
Publication Date: 1/1/2017
Citation: Turner, A.P., Jackson, J.J., Koeninger, N.K., McNeill, S.G., Montross, M.D., Casada, M.E., Boac, J.M., Bhadra, R., Maghirang, R.G., Thompson, S.A. 2017. Technical Note: Stored grain volume measurement using a low density point cloud. Applied Engineering in Agriculture. 33(1):105-112. doi:10.13031/aea.11870.

Interpretive Summary: The mass of stored grain is often determined from volume measurements by crop insurers, government auditors, and stored grain managers conducting inventories. The recent, rapid increase in bin sizes has caused greater difficulty in measuring bin volumes compared to smaller bins, particularly for accurately estimating bin surface profiles relative to standard cones. We addressed this problem by developing a new apparatus and data processing method to accurately estimate the volume of stored grain in a bin by accounting for the variability in surface topography that occurs in large diameter bins when partially unloaded. A low-cost, portable bin surface mapping system was developed to measure the grain surface using a laser distance meter, tablet PC, and ArcMap software. This manually controlled system was designed to hold the laser distance meter and provided a common reference point. Measurement of an empty hopper bottom bin (4.6 m in diameter and 6.5m tall) demonstrated the system was able to measure a known volume within 0.02%. The system was shown to capture complex surfaces well, but can be limited in the case of fill scenarios where the field of view does not include the entire grain surface.

Technical Abstract: The mass of stored grain is often determined from volume measurements by crop insurers, government auditors, and stored grain managers conducting inventories. Recent increases in bin size have accentuated the difficulty of accounting for irregularities and variations in surface conditions in calculating the volume of the grain. This study developed a new apparatus and data processing method to accurately estimate the volume of stored grain in a bin. This new method accounts for the variability in surface topography that occurs in large diameter bins when partially unloaded. A laser distance meter was used 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 6.5m tall) demonstrated the system was able to measure a known volume within 0.02%. Two applications are presented that highlight the system’s ability to capture complex surfaces, as well as limitations that result from fill scenarios where the field of view is limited.