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2023 Vol.16, Issue 4 Preview Page

Original Article

A Study on the Surface Damage Detection Method of the Main Tower of a Special Bridge Using Drones and A.I.

드론과 A.I.를 이용한 특수교 주탑부 표면 손상 탐지 방법 연구

Sungjin Lee1
,
Bongchul Joo2*
,
Jungho Kim3
,
Taehee Lee4
이 성진1
,
주 봉철2*
,
김 정호3
,
이 태희4
1Postdoctoral Researcher, Department of Structural Engineering Research, Korea Institute of Civil Engineering and Building Technology
2Senior Researcher, Department of Structural Engineering Research, Korea Institute of Civil Engineering and Building Technology
3Senior Research Fellow, Department of Structural Engineering Research, Korea Institute of Civil Engineering and Building Technology
4Manager, R&D Institute, Infrastructure Engineering Team, LOTTE Engineering & Construction
1한국건설기술연구원 구조연구본부 박사후연구원
2한국건설기술연구원 구조연구본부 수석연구원
3한국건설기술연구원 구조연구본부 선임연구위원
4롯데건설 기술연구원 토목기술연구팀 책임
*Corresponding Author
31 December 2023. pp. 129-136
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Abstract

A special offshore bridge with a high pylon has special structural features.Special offshore bridges have inspection blind spots that are difficult to visually inspect. To solve this problem, safety inspection methods using drones are being studied. In this study, image data of the pylon of a special offshore bridge was acquired using a drone. In addition, an artificial intelligence algorithm was developed to detect damage to the pylon surface. The AI algorithm utilized a deep learning network with different structures. The algorithm applied the stacking ensemble learning method to build a model that formed the ensemble and collect the results.

Keywords
Sea-crossing bridge
Cable-stayed bridge
Blind spot
Drone
Artificial intelligence

높은 주탑을 가지는 해상특수교량은 특수한 구조적 특징으로 인해 육안점검이 어려운 점검사각지대가 존재하게 되며, 이를 해결하기 위해 드론을 활용한 안전점검 방법들이 연구되고 있다. 본 연구에서는 드론을 이용하여 해상특수교량 주탑의 영상 데이터를 취득하고, 인공지능 알고리즘을 개발하여 주탑부 표면 손상에 대한 탐지를 수행하였다. 인공지능 알고리즘은 서로 다른 구조를 지닌 딥러닝 네트워크를 활용하여 앙상블을 형성한 모델을 구축하고 결과를 취합하는 스태킹 앙상블 학습법을 적용하였다.

키워드
해상특수교량
사장교
점검사각지대
드론
인공지능
References
1
Choi, Dae-Young, Seung-Hyun Paik, Young-Kyu Kim, Sang-Woo Jung, and Dae-Nyeon Kim. (2021). Deep-Learning Crack Analysis for Visual-Safety Inspection of Bridge by Drones. Journal of KIIT. 19(12): 115-121. 10.14801/jkiit.2021.19.12.115
2
Jung, Seo-Young, Seul-Ki Lee, Chan-Il Park, Soo-Young Cho, and Jung-Ho Yu. (2019). A Method for Detecting Concrete Cracks Using Deep-Learning and Image Processing. Journal of the Architectural Institute of Korea Structure & Construction. 35(11): 163-170. 10.5659/JAIK_SC.2019.35.11.163
3
Korea Agency for Infrastructure Technology Advancement. (2020). Development of Rapid Diagnosis and Evaluation Technology for Bridge Structures Based on Unmanned Inspection Equipment (No. 19SCIP-C116873-04). Anyang: KAIA.
4
Korea Institute of Civil Engineering and Building Technology. (2021). Inspection Technology at Blind Spot of Sea-Crossing Bridge Utilizing Drone and A.I. (KICT 2021-104). Goyang: KICT.
5
Lee, Suk-Bae, Ki-Hong Lee, Hyun-Min Choi and Chi-Sung Lim. (2022). Establishment of a Standard Procedure for Safety Inspections of Bridges Using Drones. Journal of Civil and Environmental Engineering Research. 42(2): 281-290. 10.12652/Ksce.2022.42.2.0281
6
Lee, Teahee, Jung-Ho Kim, Sung-Jin Lee, Seung-Ki Ryu, and Bong-Chul Joo. (2023). Improvement of Concrete Crack Segmentation Performance Using Stacking Ensemble Learning. Applied Sciences. 13: 2367. 10.3390/app13042367
7
National Geographic Information Institute. (2018). Guidelines for the Public Survey Using UAV (No. 2018-1075). Suwon: NGII.
8
Park, Ho-Young, Gyeong-Min Lee, Myoung-Hwan Han and Si-Jun Kim. (2019). Structure Safety Inspection Using Drones. Journal of the Korean Association for Spatial Structure. 19(4): 8-13.
9
Yeo, Chang-Jae and Jung-Ho Yu. (2018). A Present and Future: Facility Inspection Using Drone. Review of Architecture and Building Science. 63(06): 33-36.

Korean References Translated from the English

1
국토교통과학기술진흥원 (2020). 무인검사장비 기반 교량구조물 신속진단 및 평가기술 개발(No. 19SCIP-C116873-04). 안양: 국토교통과학기술진흥원.
2
국토지리정보원 (2018). 무인비행장치 이용 공공측량 작업지침(No. 2018-1075). 수원: 국토지리정보원.
3
박호영, 이경민, 한명환, 김시준 (2019). 구조물 안전 진단과 드론의 활용. 한국공간구조학회지. 19(4): 8-13.
4
여창재, 유정호 (2018). 드론을 활용한 시설물 상태점검 현황과 미래. 건축(대한건축학회지). 62(06): 33-36.
5
이석배, 이기홍, 최현민, 임치성 (2022). 드론 활용 교량 안전점검을 위한 표준절차 정립. 대한토목학회 논문집. 42(2): 281-290. 10.12652/Ksce.2022.42.2.0281
6
정서영, 이슬기, 박찬일, 조수영, 유정호 (2019). 딥러닝 및 영상처리 기술을 활용한 콘크리트 균열 검출 방법. 대한건축학회 논문집. 35(11): 163-170. 10.5659/JAIK_SC.2019.35.11.163
7
최대영, 백승현, 김영규, 정상우, 김대년 (2021). 드론 활용 교량 안전점검을 위한 딥러닝 균열 분석에 관한 연구. 한국정보기술학회 논문지. 19(12): 115-121. 10.14801/jkiit.2021.19.12.115
8
한국건설기술연구원 (2021). 드론과 A.I.를 이용한 해상특수교량 점검사각지대 해소 기술(KICT 2021-104). 고양: 한국건설기술연구원.
Information
  • Publisher :Korean Society of Disaster and Security
  • Publisher(Ko) :한국방재안전학회
  • Journal Title :Journal of Korean Society of Disaster and Security
  • Journal Title(Ko) :한국방재안전학회 논문집
  • Volume : 16
  • No :4
  • Pages :129-136
  • Received Date : 2023-11-25
  • Revised Date : 2023-12-15
  • Accepted Date : 2023-12-18
  • DOI :https://doi.org/10.21729/ksds.2023.16.4.129
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