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dc.contributor.advisorLi, Jian
dc.contributor.authorKONG, XIANGXIONG
dc.date.accessioned2019-05-07T16:40:02Z
dc.date.available2019-05-07T16:40:02Z
dc.date.issued2018-12-18
dc.date.submitted2019
dc.identifier.otherhttp://dissertations.umi.com/ku:16169
dc.identifier.urihttp://hdl.handle.net/1808/27812
dc.description.abstractFatigue cracks that develop in steel highway bridges under repetitive traffic loads are one of the major mechanisms that degrades structural integrity. If bridges are not appropriately inspected and maintained, fatigue cracks can eventually lead to catastrophic failures, in particular for fracture-critical bridges. Despite various levels of success of crack monitoring methods over the past decades in the fields of structural health monitoring (SHM) and non-destructive evaluation (NDE), monitoring fatigue cracks in steel bridges is still challenging due to the complex structural joint layout and unpredictable crack propagation paths. In this dissertation, advanced SHM technologies are proposed for detecting and monitoring fatigue cracks in steel bridges. These technologies are categorized as: 1) a large-area strain sensing technology based on the soft elastomeric capacitor (SEC) sensor; and 2) non-contact vision-based fatigue crack detection approaches. In SEC-based fatigue crack sensing, the research focuses are placed on numerical prediction of the SEC’s response under fatigue cracking and experimental validations of sensing algorithms for monitoring fatigue cracks over long-term. In vision-based fatigue crack detection approaches, two novel sensing methodologies are established through feature tracking and image overlapping, respectively. Laboratory test results verified that the proposed approaches can robustly identify the true fatigue crack from many non-crack edges. Overall, the proposed advanced SHM technologies show great promise for fatigue crack damage detection of steel bridges in laboratory configurations, hence form the basis for long-term fatigue sensing solutions in field applications.
dc.format.extent163 pages
dc.language.isoen
dc.publisherUniversity of Kansas
dc.rightsCopyright held by the author.
dc.subjectCivil engineering
dc.subjectcomputer vision
dc.subjectfatigue crack
dc.subjectsensing skin
dc.subjectsoft elastomeric capacitor
dc.subjectsteel bridge
dc.subjectstructural health monitoring
dc.titleMonitoring Fatigue Cracks in Steel Bridges using Advanced Structural Health Monitoring Technologies
dc.typeDissertation
dc.contributor.cmtememberBennett, Caroline
dc.contributor.cmtememberCollins, William
dc.contributor.cmtememberLaflamme, Simon
dc.contributor.cmtememberFadden, Matthew
dc.contributor.cmtememberFang, Huazhen
dc.thesis.degreeDisciplineCivil, Environmental & Architectural Engineering
dc.thesis.degreeLevelPh.D.
dc.identifier.orcid0000-0001-5134-7432
dc.rights.accessrightsembargoedAccess


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