Detection and estimation of damage in framed structures using modal data

dc.contributor.authorDe Silva, WARK
dc.contributor.authorLewangamage, CS
dc.contributor.authorJayasinghe, MTR
dc.date.accessioned2019-10-22T05:55:57Z
dc.date.available2019-10-22T05:55:57Z
dc.description.abstractThe inevitable ageing and degradation of buildings and the structural failures that follow, have ignited a need for early prognosis of probable structural failures so that proactive measures can be undertaken. Hence, one of the important steps of structural health monitoring (SHM) process is the detection of damage location and estimation of damage severity. Modal data can be effectively used for this purpose owing to their sole dependency on mechanical characteristics of a structure. This study presents a damage detection methodology based on mode shape derivatives such as mode shape slope (MSS) and mode shape curvature (MSC) for a symmetric experimental steel frame model. Furthermore, an extended parametric analysis has been performed using a calibrated finite element model to investigate damage localization and quantify severity. The study provides key conclusions about the effect of boundaries on the damage detection method for the steel frame model. Furthermore, damage detection using MSC is identified to be more sensitive as opposed to MSS method.en_US
dc.identifier.conferenceMoratuwa Engineering Research Conference - MERCon 2019en_US
dc.identifier.departmentDepartment of Civil Engineeringen_US
dc.identifier.facultyEngineeringen_US
dc.identifier.placeMoraruwa, Sri Lankaen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/15171
dc.identifier.year2019en_US
dc.language.isoenen_US
dc.subjectStructural health monitoringen_US
dc.subjectModal based damage detectionen_US
dc.subjectDamage localizationen_US
dc.subjectDamage severityen_US
dc.subjectFrame structure,en_US
dc.subjectShaking tableen_US
dc.subjectFinite element modelen_US
dc.titleDetection and estimation of damage in framed structures using modal dataen_US
dc.typeConference-Abstracten_US

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