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선박 및 플랜트 구조물 치수품질 검사를 위한 스캔데이터 분석 방법

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dc.contributor.author권대용-
dc.contributor.author윤여운-
dc.contributor.author최두진-
dc.contributor.author권기연-
dc.date.available2020-12-21T06:40:07Z-
dc.date.created2020-12-21-
dc.date.issued2020-
dc.identifier.issn2508-4003-
dc.identifier.urihttps://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/18523-
dc.description.abstractPlant equipment is made at the factory and installed at the construction site. If dimension quality problems occur during this process, it is impossible to fix the equipment. The part that is already installed at the construction site will need to be modified. Such modifications are expensive and time consuming. Dimensional quality inspection is required in advance and, recently, 3D laser scanners have been used. These can measure large areas more quickly than possible using other measuring instruments; however, 3D laser scanner results require a great deal of post-processing. In this study, we propose a method that automatically analyzes measured point data for dimension quality inspection of plant equipment. To reduce the calculation time, a grid is constructed and dimensional quality analysis is performed using representative points. Also, to remove noise and unnecessary areas, points with large error are repeatedly deleted.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국CDE학회-
dc.title선박 및 플랜트 구조물 치수품질 검사를 위한 스캔데이터 분석 방법-
dc.title.alternativeScan Data Analysis Method for Dimension Quality Inspection of Structures in Shipbuilding and Plant Construction-
dc.typeArticle-
dc.contributor.affiliatedAuthor권기연-
dc.identifier.doi10.7315/CDE.2020.406-
dc.identifier.bibliographicCitation한국CDE학회 논문집, v.25, no.4, pp.406 - 416-
dc.relation.isPartOf한국CDE학회 논문집-
dc.citation.title한국CDE학회 논문집-
dc.citation.volume25-
dc.citation.number4-
dc.citation.startPage406-
dc.citation.endPage416-
dc.type.rimsART-
dc.identifier.kciidART002653082-
dc.description.journalClass2-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthor3D laser scanner-
dc.subject.keywordAuthorDimensional quality inspection-
dc.subject.keywordAuthorPlant equipment-
dc.subject.keywordAuthorPoint cloud-
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