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Motion Magnification Analysis for structural monitoring of ancient constructions

TitoloMotion Magnification Analysis for structural monitoring of ancient constructions
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2018
AutoriFioriti, Vincenzo, Roselli Ivan, Tatì Angelo, Romano S, and De Canio Gerardo
RivistaMeasurement: Journal of the International Measurement Confederation
Volume129
Paginazione375-380
ISSN02632241
Parole chiaveDynamic identification, Frequency domain analysis, Historic structures, Laser vibrometers, Modal analysis, Modal identification, Motion analysis, Motion Magnification, Optimization, Small displacement, Structural monitoring, Velocimeters, Velocity measurement, Vibration analysis, Vibration measurement, Vibration monitoring
Abstract

A new methodology for digital image processing, namely the Motion Magnification (MM), allows to magnify small displacements of large structures. MM acts like a microscope for motion in video sequences, but affecting only some groups of pixels. The processed videos unveil motions hardly visible with the naked eye and allow a more effective frequency domain analysis. We applied the MM method to several historic structures, including a 1:10-scale mockup of Hagia Irene in Constantinople tested on shaking table, the so-called Temple of Minerva Medica in Rome and the Ponte delle Torri of Spoleto. MM algorithms parameters were calibrated by comparison with reference consolidated modal identification methods applied to conventional velocimeters data. Encouraging results were obtained in terms of vibration monitoring and modal analysis for dynamic identification of the studied structures, offering a low-cost, viable support to the standard vibration sensing equipment, such as contact velocimeters, laser vibrometers and others. © 2018

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85050296812&doi=10.1016%2fj.measurement.2018.07.055&partnerID=40&md5=68797ec1ef92b059a7bbcb179d3bfab9
DOI10.1016/j.measurement.2018.07.055
Citation KeyFioriti2018375