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dc.contributor.authorPeng, Zhen
dc.contributor.supervisorJun Lien_US
dc.contributor.supervisorHong Haoen_US
dc.date.accessioned2022-07-29T06:40:11Z
dc.date.available2022-07-29T06:40:11Z
dc.date.issued2022en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/89064
dc.description.abstract

This thesis focuses on developing novel data analytics and damage detection methods that are applicable to the condition assessment of civil engineering structures subjected to operational and environmental condition changes, nonlinearity and/or measurement noise. Comprehensive numerical and experimental studies validate the effectiveness and performance of using the proposed approaches for practical structural health monitoring applications.

en_US
dc.publisherCurtin Universityen_US
dc.titleNovel Data Analytics for Developing Sensitive and Reliable Damage Indicators in Structural Health Monitoringen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Civil and Mechanical Engineeringen_US
curtin.accessStatusFulltext not availableen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidPeng, Zhen [0000-0001-9352-9613]en_US
dc.date.embargoEnd2024-07-28


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