인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
학술저널
Full-text XML
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
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초록·키워드
One of the most prevalent maritime accidents that continues to occur is the loss of stability. This issue is particularly common in RoRo or RoPax ships, which have a high center of gravity. Due to the nature of these ships, which transport vehicles, it is difficult to accurately estimate stability because the cargo weight and loading positions are not standardized. Therefore, this study proposes a method to improve the loading computer using image recognition technology. First, the axle load of cargo vehicles waiting to board the ship is measured. Second, the vehicle's license plate and type are recognized. The position of the vehicles is then tracked using the recognized license plate information and cameras mounted on each deck and ramp. Finally, once the vehicle stops, this information is transmitted to the loading computer. We applied the proposed method to RoPax vessels to evaluate their effectiveness. We modeled a total of two decks and loaded 60 vehicles to verify whether the positions of these vehicles were accurately received by the loading computer through interface. loading plan was then utilized to assess the ship's stability. This confirmed that the proposed method can be used to improve the accuracy of stability assessments by eliminating human error. As a result, more precise and reliable evaluations of a ship's stability can be achieved using proposed approach.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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