Development of a bulk material volume estimation system using automatic moving rail LiDAR technology




Bulk material, Volume estimation, LiDAR technology, Point cloud data


This paper focuses on developing a bulk material volume estimation system employing automatic moving rail optical distance measuring technology. The research objective is to devise a system capable of estimating warehouse bulk material volumes utilizing point cloud data. Additionally, the research proposes guidelines for enhancing efficiency in bulk material volume estimation processes. A prototype system was developed and tested using dry rice husk with a humidity level of 15% as the sample material. The testing environment comprised a laboratory with dimensions of 36 square meters and a height of 3 meters, wherein the sample material was arranged in a cone shape with a volume of 1 cubic meter. The system was designed to test with movement speed range from 2 to 30 centimeters per second, and the scanning angles of 0, 45, and 90 degrees. Statistical principles were applied to analyze the collected data, determining averages, and comparing results with actual data to assess accuracy and precision in volumetric measurements. Furthermore, the research evaluated the advantages and disadvantages of alternative tools for bulk material volume estimation in comparison to the developed system, considering factors such as data collection duration, operational costs, and safety measures. Experimental results revealed that at a scanning angle of 90 degrees and a moving speed of 20 centimeters per second achieve a volumetric data accuracy of 97%.


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How to Cite

C. Sritap, P. Pitayachaval, and S. Tantrairatn, “Development of a bulk material volume estimation system using automatic moving rail LiDAR technology”, J. Appl. Methods Electron. Comput., vol. 12, no. 2, pp. 48–53, Jun. 2024.



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