Stored grain volume measurement using a low density point cloud

A. P. Turner; J. J. Jackson; N. K. Koeninger; S. G. McNeill; M. D. Montross; M. E. Casada; J. M. Boac; R. Bhadra; R. G. Maghirang; S. A. Thompson

doi:10.13031/aea.11870

Stored grain volume measurement using a low density point cloud

A. P. Turner, J. J. Jackson, N. K. Koeninger, S. G. McNeill, M. D. Montross, M. E. Casada, J. M. Boac, R. Bhadra, R. G. Maghirang, S. A. Thompson

Biosystems and Agricultural Engineering

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	105-112
Number of pages	8
Journal	Applied Engineering in Agriculture
Volume	33
Issue number	1
DOIs	https://doi.org/10.13031/aea.11870
State	Published - 2017

Bibliographical note

Funding Information:
The research was supported by the USDA (CRIS No. 5430-43440-007-08R and RMA Agreement No. 09-IA- 0831-0096). This is publication No. 15-05-073 of the Kentucky Agricultural Experiment Station and is published with the approval of the Director. This work is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch-Multistate under 1002344. The assistance provided by Will Adams, Drew Schiavone, and Carla Rodrigues (University of Kentucky) in the development of the measurement system is highly appreciated. Additionally, the authors would like to thank Chuck Kunisch (Michigan Agricultural Commodities, Brown City, Mich.) and Andy Shaffner (Shaffner Brothers Farm, Midland, Mich.) for allowing us to use their facilities to conduct this research.

Publisher Copyright:
© 2017 American Society of Agricultural and Biological Engineers.

Keywords

Grain surface
Spatial modeling
Stored grain management

ASJC Scopus subject areas

Engineering (all)

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10.13031/aea.11870

Cite this

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title = "Stored grain volume measurement using a low density point cloud",

abstract = "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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author = "Turner, {A. P.} and Jackson, {J. J.} and Koeninger, {N. K.} and McNeill, {S. G.} and Montross, {M. D.} and Casada, {M. E.} and Boac, {J. M.} and R. Bhadra and Maghirang, {R. G.} and Thompson, {S. A.}",

note = "Funding Information: The research was supported by the USDA (CRIS No. 5430-43440-007-08R and RMA Agreement No. 09-IA- 0831-0096). This is publication No. 15-05-073 of the Kentucky Agricultural Experiment Station and is published with the approval of the Director. This work is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch-Multistate under 1002344. The assistance provided by Will Adams, Drew Schiavone, and Carla Rodrigues (University of Kentucky) in the development of the measurement system is highly appreciated. Additionally, the authors would like to thank Chuck Kunisch (Michigan Agricultural Commodities, Brown City, Mich.) and Andy Shaffner (Shaffner Brothers Farm, Midland, Mich.) for allowing us to use their facilities to conduct this research. Publisher Copyright: {\textcopyright} 2017 American Society of Agricultural and Biological Engineers.",

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AU - Jackson, J. J.

AU - Koeninger, N. K.

AU - McNeill, S. G.

AU - Montross, M. D.

AU - Casada, M. E.

AU - Boac, J. M.

AU - Bhadra, R.

AU - Maghirang, R. G.

AU - Thompson, S. A.

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PY - 2017

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N2 - 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.

AB - 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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Stored grain volume measurement using a low density point cloud

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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