State-of-the-art technologies for UAV inspections
Visual condition inspections serve as the basis for determining the need and schedule for service tasks such as maintenance and remediation projects to preserve the proper functioning of power facilities and infrastructure. An increasing accumulation of service projects has recently surfaced due to...
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Published in | IET radar, sonar & navigation Vol. 12; no. 2; pp. 151 - 164 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
The Institution of Engineering and Technology
01.02.2018
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Subjects | |
Online Access | Get full text |
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Summary: | Visual condition inspections serve as the basis for determining the need and schedule for service tasks such as maintenance and remediation projects to preserve the proper functioning of power facilities and infrastructure. An increasing accumulation of service projects has recently surfaced due to the lengthy, labour-intensive and subjective qualities of the current method for inspection. These processes are also costly due to the temporary closure of the infrastructure as well as the requirement of special inspection equipment. Unmanned aerial vehicles (UAVs), commonly known as drones, offer potential as a useful tool for infrastructure inspections. UAVs provide visual assessments of structures while eliminating the need for manual inspections. Thus, aerial systems have the potential to reduce the cost of inspections as well as limit the disruption of the public while allowing engineers to have a better three-dimensional understanding of the system. However, the implementation of UAV inspection includes several difficulties such as flight stability, control accuracy, and safety. This study summarises the context for UAV inspection of power facilities and structures. Technologies to address the hindrances preventing UAV integration into the current practice are reviewed. Existing challenges and future work in research for UAV inspections are also presented. |
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ISSN: | 1751-8784 1751-8792 1751-8792 |
DOI: | 10.1049/iet-rsn.2017.0251 |