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Investigation on Applicability and Limitation of Cosine Similarity-Based Structural Condition Monitoring for Gageocho Offshore Structure

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dc.contributor.authorKim, B.-
dc.contributor.authorOh, J.-
dc.contributor.authorMin, C.-
dc.date.accessioned2023-12-22T09:32:04Z-
dc.date.available2023-12-22T09:32:04Z-
dc.date.issued2022-01-
dc.identifier.issn1424-8220-
dc.identifier.issn1424-3210-
dc.identifier.urihttps://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/9302-
dc.description.abstractThe key to coping with global warming is reconstructing energy governance from carbon-based to sustainable resources. Offshore energy sources, such as offshore wind turbines, are promising alternatives. However, the abnormal climate is a potential threat to the safety of offshore structures because construction guidelines cannot embrace climate outliers. A cosine similarity-based maintenance strategy may be a possible solution for managing and mitigating these risks. However, a study reporting its application to an actual field structure has not yet been reported. Thus, as an initial study, this study investigated whether the technique is applicable or whether it has limitations in the real field using an actual example, the Gageocho Ocean Research Station. Consequently, it was found that damage can only be detected correctly if the damage states are very similar to the comparison target database. Therefore, the high accuracy of natural frequencies, including environmental effects, should be ensured. Specifically, damage scenarios must be carefully designed, and an alternative is to devise more efficient techniques that can compensate for the present procedure. ? 2022 by the authors. Licensee MDPI, Basel, Switzerland.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleInvestigation on Applicability and Limitation of Cosine Similarity-Based Structural Condition Monitoring for Gageocho Offshore Structure-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/s22020663-
dc.identifier.scopusid2-s2.0-85122878606-
dc.identifier.wosid000758810400001-
dc.identifier.bibliographicCitationSensors, v.22, no.2-
dc.citation.titleSensors-
dc.citation.volume22-
dc.citation.number2-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordPlusDAMAGE DETECTION-
dc.subject.keywordPlusCORROSION-FATIGUE-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusWIND-
dc.subject.keywordPlusJOINTS-
dc.subject.keywordAuthorCosine similarity-
dc.subject.keywordAuthorDamage detection-
dc.subject.keywordAuthorGageocho Ocean Research Station-
dc.subject.keywordAuthorStructural health monitoring-
dc.subject.keywordAuthorStructural integrity assessment-
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