A UAV-based framework for semi-automated thermographic inspection of belt conveyors in the mining industry.
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Date
2020
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Abstract
Frequent and accurate inspections of industrial components and equipment are essential because failures can cause unscheduled downtimes, massive material, and financial losses or even endanger workers. In the mining industry, belt idlers or rollers are examples of such critical components. Although there are many precise laboratory techniques to assess the condition of a roller, companies still have trouble implementing a reliable and scalable procedure to inspect their field assets. This article enumerates and discusses the existing roller inspection techniques and presents a novel approach based on an Unmanned Aerial Vehicle (UAV) integrated with a thermal imaging camera. Our preliminary results indicate that using a signal processing technique, we are able to identify roller failures automatically. We also proposed and implemented a back-end platform that enables field and cloud connectivity with enterprise systems. Finally, we have also cataloged the anomalies detected during the extensive field tests in order to build a structured dataset that will allow for future experimentation.
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Keywords
Idler rollers, Computer vision, Maintenance
Citation
CARVALHO JÚNIOR, J. R. de et al. A UAV-based framework for semi-automated thermographic inspection of belt conveyors in the mining industry. Sensors, v. 20, artigo 2243, 2020. Disponível em: <https://www.mdpi.com/1424-8220/20/8/2243>. Acesso em: 25 agosto 2021.