Young Researcher Paper Award 2021

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Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Economical Inspection Methods Assisted by Unmanned Aerial Vehicle for Bridges in Korea

HyunSang Choi, JaeKang Lee, and JungOk Kim

(Received November 23, 2021; Accepted July 21, 2022)

Keywords: bridge, maintenance and inspection, crack detection, water leak, white coating, UAV

Current infrastructure maintenance works face limitations caused for various reasons: insufficient budget, increasing number of infrastructure facilities requiring maintenance, shortage of labor, and rapidly increasing number of aged infrastructure facilities. To overcome these limitations, a new approach is required that is different from manual inspection methods under existing rules and regulations. In this context, in this study we explored the efficiency of bridge inspection and maintenance by unmanned aerial vehicles (UAVs), which can observe inaccessible areas, be conveniently and easily controlled, and may offer high economic benefits. Various tests were performed on elevated bridges and suitable UAV images were obtained. The obtained images were inspected using machine vision technology, thereby avoiding subjective evaluations by humans. We also discuss methods for enhancing the objectivity of inspections. Another aim of this study was to automate inspection work and improve work efficiency through computer vision technology. The UAV image analysis and classification technology in this study utilized existing computer vision technology, but the optimization process for each inspection item is described in detail so that it can be directly applied to the inspection task. This is to overcome limitations of current inspection tasks, which require the ability and experience of personnel. For this purpose, objectivity can be secured by optimizing the data acquisition and analysis process on a job-by-job basis. The test results showed that both the efficiency and objectivity of the proposed UAV-based method were superior to those of existing bridge maintenance and inspection methods.

Corresponding author: HyunSang Choi, JaeKang Lee

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