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Parametric comparing for local inspection of industrial plants by using as-built model acquired from laser scan data

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dc.contributor.authorNguyen, C.H.P.-
dc.contributor.authorChoi, Y.-
dc.date.available2019-03-08T06:57:33Z-
dc.date.issued2018-03-04-
dc.identifier.issn1686-4360-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/3366-
dc.description.abstractOwing to the increasing complexity of modern industrial plants such as naval and ocean plants and industrial factories, it is very urgent to have an efficient method for inspecting such structures in terms of as-built inspection and maintenance. In this paper, we propose a method called ‘parametric comparing’ which utilizes laser scan technology to support the inspection process of industrial plants. In our approach, component parameters are extracted from laser scan data and then compared with their as-designed parameters. The results of this process can support engineers to assess the quality of the as-built model. Because most components in an industrial plant could be classified as piping elements, we focus on two classes of components: straight pipes and connecting components. Validations on two prototype data sets have proved that our approach is practical and fit for industrial application. © 2017 CAD Solutions, LLC.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherTaylor and Francis Inc.-
dc.titleParametric comparing for local inspection of industrial plants by using as-built model acquired from laser scan data-
dc.typeArticle-
dc.identifier.doi10.1080/16864360.2017.1375675-
dc.identifier.bibliographicCitationComputer-Aided Design and Applications, v.15, no.2, pp 238 - 246-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85030168926-
dc.citation.endPage246-
dc.citation.number2-
dc.citation.startPage238-
dc.citation.titleComputer-Aided Design and Applications-
dc.citation.volume15-
dc.type.docTypeArticle-
dc.publisher.location미국-
dc.subject.keywordAuthorlocal inspection-
dc.subject.keywordAuthorParametric comparing-
dc.subject.keywordAuthorpoint cloud processing-
dc.description.journalRegisteredClassscopus-
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