Laboratory tests on local damage detection for jacket-type offshore structures using optical FBG sensors based on statistical approaches SCIE SCOPUS

DC Field Value Language Yi, Jin-Hak - 2020-04-16T13:40:08Z - 2020-04-16T13:40:08Z - 2020-01-28 - 2016-09-15 -
dc.identifier.issn 0029-8018 -
dc.identifier.uri -
dc.description.abstract In this study, a local damage detection based on statistical approach for jacket-type offshore structures by principal component analysis (PCA) and linear adaptive filter (LAF) techniques using strain response data measured by FBG sensors was proposed while dynamic responses are being popularly utilized for damage detection of civil infrastructures including jacket-type offshore structures. In addition, environmental effects due to variations in temperature and external loading were intensively investigated and an efficient remedy was proposed using the nonparametric PCA and LAF models. Unlike many existing statistical damage detection methods, the mean of residual values eliminating the environmental effects was utilized as damage index for rational for enhancing the normality based on the central limit theorem and the normality was first checked before damage estimation using the mean of residual values. Laboratory tests for a scaled tidal current power plant structure, one of many jacket-type offshore structures, were conducted to investigate the technical feasibility of the proposed method for damage detection and localization. It was found that the PCA technique could more efficiently eliminate undesired environmental effects contained in the measurement data from FBG sensors without any additional information on the environmental changes, resulting in more damage-sensitive features under various environmental changes. (C) 2016 Elsevier Ltd. All rights reserved. -
dc.description.uri 1 -
dc.language English -
dc.subject PLATFORMS -
dc.subject RESPONSES -
dc.subject BRIDGE -
dc.subject MODEL -
dc.title Laboratory tests on local damage detection for jacket-type offshore structures using optical FBG sensors based on statistical approaches -
dc.type Article -
dc.citation.endPage 103 -
dc.citation.startPage 94 -
dc.citation.title OCEAN ENGINEERING -
dc.citation.volume 124 -
dc.identifier.bibliographicCitation OCEAN ENGINEERING, v.124, pp.94 - 103 -
dc.identifier.doi 10.1016/j.oceaneng.2016.07.060 -
dc.identifier.scopusid 2-s2.0-84979979872 -
dc.identifier.wosid 000383813600009 -
dc.type.docType Article -
dc.description.journalClass 1 -
dc.subject.keywordPlus IDENTIFICATION -
dc.subject.keywordPlus PLATFORMS -
dc.subject.keywordPlus RESPONSES -
dc.subject.keywordPlus BRIDGE -
dc.subject.keywordPlus MODEL -
dc.subject.keywordAuthor Jacket structure -
dc.subject.keywordAuthor Fiber Bragg grating sensor -
dc.subject.keywordAuthor Linear adaptive filter model -
dc.subject.keywordAuthor Principal component analysis model -
dc.subject.keywordAuthor Statistical damage assessment -
dc.relation.journalWebOfScienceCategory Engineering, Marine -
dc.relation.journalWebOfScienceCategory Engineering, Civil -
dc.relation.journalWebOfScienceCategory Engineering, Ocean -
dc.relation.journalWebOfScienceCategory Oceanography -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Engineering -
dc.relation.journalResearchArea Oceanography -
Appears in Collections:
Coastal & Ocean Engineering Division > Coastal Development and Ocean Energy Research Center > 1. Journal Articles
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