Autonomous Alignment Monitoring for Large-Scale Conveyor Systems Using UAVs, Photogrammetry, and Machine Learning
Publication: Computing in Civil Engineering 2021
ABSTRACT
Support structures of relocatable large-scale outdoor conveyor systems are prone to unintended movements over time due to vibration induced by their moving parts, as well as the usually non-solid foundation ground. These movements can lead to a misalignment of the system’s individual segments, which in turn can cause an increase in power consumption as well as a potential belt ripping and therefore a breakdown of the system. This article proposes a novel approach to autonomously monitor the alignment of large-scale conveyor systems utilizing aerial images captured via unmanned aerial vehicles, semantic image segmentation via deep learning, 2D-to-3D label transfer using photogrammetry, and 3D point cloud analysis. The feasibility of the method is demonstrated on a working prototype. One of the main challenges is to find a good balance between precision and reliability on the one hand and computational costs on the other.
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Computing in Civil Engineering 2021
Pages: 148 - 155
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Published online: May 24, 2022
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