Acknowledgement
이 논문은 2022년도 해양수산부 및 해양수산과학기술진흥원 연구비 지원으로 수행된 '자율운항선박 기술개발사업(20200615)'의 연구결과입니다.
Journal of the Society of Naval Architects of Korea (대한조선학회논문집)
- Volume 59 Issue 4
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- Pages.235-242
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- 2022
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- 1225-1143(pISSN)
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- 2287-7355(eISSN)
DOI QR Code
Application of Point Cloud Based Hull Structure Deformation Detection Algorithm
포인트 클라우드 기반 선체 구조 변형 탐지 알고리즘 적용 연구
- Song, Sang-ho (Digitalization Team, Korean Register) ;
- Lee, Gap-heon (Digitalization Team, Korean Register) ;
- Han, Ki-min (Digitalization Team, Korean Register) ;
- Jang, Hwa-sup (Digitalization Team, Korean Register)
- 송상호 ((사)한국선급 디지털라이제이션팀) ;
- 이갑헌 ((사)한국선급 디지털라이제이션팀) ;
- 한기민 ((사)한국선급 디지털라이제이션팀) ;
- 장화섭 ((사)한국선급 디지털라이제이션팀)
- Received : 2022.07.05
- Accepted : 2022.07.25
- Published : 2022.08.20
Abstract
As ship condition inspection technology has been developed, research on collecting, analyzing, and diagnosing condition information has become active. In ships, related research has been conducted, such as analyzing, detecting, and classifying major hull failures such as cracks and corrosion using 2D and 3D data information. However, for geometric deformation such as indents and bulges, 2D data has limitations in detection, so 3D data is needed to utilize spatial feature information. In this study, we aim to detect hull structural deformation positions. It builds a specimen based on actual hull structure deformation and acquires a point cloud from a model scanned with a 3D scanner. In the obtained point cloud, deformation(outliers) is found with a combination of RANSAC algorithms that find the best matching model in the Octree data structure and dataset.