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ID 68238
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Author
Shimizu, Yuya Okayama University
Kamegawa, Tetsushi Okayama University Kaken ID publons researchmap
Wang, Yongdong Okayama University
Tamura, Hajime Okayama University
Teshima, Taiga Okayama University
Nakano, Sota Okayama University
Tada, Yuki Okayama University
Nakano, Daiki Okayama University
Sasaki, Yuichi Okayama University
Sekito, Taiga Okayama University
Utsumi, Keisuke Okayama University
Nagao, Rai Okayama University
Semba, Mizuki Okayama University
Abstract
In this article, an approach used for the inspection tasks in the WRS2020 Plant Disaster Prevention Challenge is explained. The tasks were categorized into three categories: reading pressure gauges, inspecting rust on a tank, and inspecting cracks in a tank. For reading pressure gauges, the “you only look once” algorithm was used to focus on a specific pressure gauge and check the pressure gauge range strings on the gauge using optical character recognition algorithm. Finally, a previously learned classifier was used to read the values shown in the gauge. For rust inspection, image processes were used to focus on a target plate that may be rusted for rust detection. In particular, it was necessary to report the rust area and distribution type. Thus, the pixel ratio and grouping of rust were used to count the rust. The approach for crack inspection was similar to that for rust. The target plate was focused on first, and then the length of the crack was measured using image processing. Its width was not measured but was calculated using the crack area and length. For each system developed to approach each task, the results of the preliminary experiment and those of WRS2020 are shown. Finally, the approaches are summarized, and planned future work is discussed.
Keywords
WRS2020
image processing
auto inspection
YOLO
OCR
Published Date
2023-02-20
Publication Title
Journal of Robotics and Mechatronics
Volume
volume35
Issue
issue1
Publisher
Fuji Technology Press Ltd.
Start Page
65
End Page
73
ISSN
1883-8049
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
Copyright Holders
© Fuji Technology Press Ltd.
File Version
publisher
DOI
Web of Science KeyUT
Related Url
isVersionOf https://doi.org/10.20965/jrm.2023.p0065
License
https://creativecommons.org/licenses/by-nd/4.0/
Citation
Y. Shimizu, T. Kamegawa, Y. Wang, H. Tamura, T. Teshima, S. Nakano, Y. Tada, D. Nakano, Y. Sasaki, T. Sekito, K. Utsumi, R. Nagao, and M. Semba, “Development of Automatic Inspection Systems for WRS2020 Plant Disaster Prevention Challenge Using Image Processing,” J. Robot. Mechatron., Vol.35 No.1, pp. 65-73, 2023.