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dc.contributor.advisorOral Büyüköztürk.en_US
dc.contributor.authorChen, Justin Gejuneen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Civil and Environmental Engineering.en_US
dc.coverage.spatialn-us-nhen_US
dc.date.accessioned2016-09-13T18:06:57Z
dc.date.available2016-09-13T18:06:57Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/104119
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 257-266).en_US
dc.description.abstractFunctional infrastructure-including transportation, energy, and buildings and other facilities - is key to the economic production of a country and the daily lives of its people. Due to deterioration and potential damage, timely inspections and repairs are necessary to keep infrastructure functioning at full capacity. Visual testing is one of the oldest and most widely used methods for condition assessment; however, this technique is limited since it is based on an inspector's subjective rating rather than on an objective quantitative measure of structural condition. Quantitative alternatives to visual testing have emerged over time. These include vibration analysis, in which a structure's operational resonant frequencies and mode shapes are measured and compared against a healthy baseline to detect changes. Typically, contact sensors such as accelerometers have been used to measure vibrations. When physical access to a structure is limited or the placement of contact sensors is too time-consuming, new technologies that allow for non-contact measurements can be used. Video cameras, where each pixel is effectively a sensor, can remotely collect a large amount of data from a structure. The challenge is then to interpret these videos into quantitative vibration data. In this research, newly developed computer vision techniques for analyzing small motions in videos and their application to the vibration measurement and condition assessment of infrastructure are presented. These techniques allow for qualitative visualizations of normally imperceptible motions as a form of enhanced visual testing, and quantitative measurements of the displacements and vibrations of structures as a basis for condition assessment. Computer vision algorithms for processing video are described and the technique is experimentally validated against traditional sensors. The methodology is demonstrated with a series of laboratory measurements of simple representative structures and field measurements of civil infrastructure, including the WWI Memorial Bridge in Portsmouth, New Hampshire.en_US
dc.description.statementofresponsibilityby Justin Gejune Chen.en_US
dc.format.extent266 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleVideo camera-based vibration measurement of infrastructureen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.identifier.oclc958137131en_US


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