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http://dx.doi.org/10.14775/ksmpe.2022.21.05.046

Classification of the Rusting State of Pipe Using a Laser Displacement Sensor  

Cheon, Kang-Min (Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering of Mechanical Engineering), Kumoh National Institute of Technology)
Shin, Baek-Cheon (Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering of Mechanical Engineering), Kumoh National Institute of Technology)
Shin, Geon-Ho (Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering of Mechanical Engineering), Kumoh National Institute of Technology)
Go, Jeong-Il (Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering of Mechanical Engineering), Kumoh National Institute of Technology)
Lee, Jun-Hyeok (Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering of Mechanical Engineering), Kumoh National Institute of Technology)
Hur, Jang-Wook (Department of Mechanical Engineering (Department of Aeronautics, Mechanical and Electronic Convergence Engineering of Mechanical Engineering), Kumoh National Institute of Technology)
Publication Information
Journal of the Korean Society of Manufacturing Process Engineers / v.21, no.5, 2022 , pp. 46-52 More about this Journal
Abstract
Although pipe performs various functions in industrial sites and residential spaces, if it is damaged due to corrosion caused by the external environment, it may cause equipment failure or a major accident. For this reason, various studies for safety management are being conducted, but studies on detecting corrosion or cracks on the pipe surface using a laser displacement sensor have hardly been conducted. Therefore, in this study, the corrosion degree of the pipe surface was compared and classified into 4 corrosion conditions, and inspection equipment using a laser scanner was manufactured. The corrosion height was calculated from the four surface data obtained from the measuring equipment and applied to various CNN algorithms, and 91% accuracy was obtained during training using the Modified VGGNet16 code with reduced number of parameters.
Keywords
Pipe; Laser Displacement Sensor; Convolution Neural Network; VGGNet; State Classification;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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