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      A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking †

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          Abstract

          Advancements in optical imaging devices and computer vision algorithms allow the exploration of novel diagnostic techniques for use within engineering systems. A recent field of application lies in the adoption of such devices for non-contact vibrational response recordings of structures, allowing high spatial density measurements without the burden of heavy cabling associated with conventional technologies. This, however, is not a straightforward task due to the typically low-amplitude displacement response of structures under ambient operational conditions. A novel framework, namely Magnified Tracking (MT), is proposed herein to overcome this limitation through the synergistic use of two computer vision techniques. The recently proposed phase-based motion magnification (PBMM) framework, for amplifying motion in a video within a defined frequency band, is coupled with motion tracking by means of particle tracking velocimetry (PTV). An experimental campaign was conducted to validate a proof-of-concept, where the dynamic response of a shear frame was measured both by conventional sensors as well as a video camera setup, and cross-compared to prove the feasibility of the proposed non-contact approach. The methodology was explored both in 2D and 3D configurations, with PTV revealing a powerful tool for the measurement of perceptible motion. When MT is utilized for tracking “imperceptible” structural responses (i.e., below PTV sensitivity), via the use of PBMM around the resonant frequencies of the structure, the amplified motion reveals the operational deflection shapes, which are otherwise intractable. The modal results extracted from the magnified videos, using PTV, demonstrate MT to be a viable non-contact alternative for 3D modal identification with the benefit of a spatially dense measurement grid.

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          Most cited references61

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          Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                11 March 2019
                March 2019
                : 19
                : 5
                : 1229
                Affiliations
                [1 ]Institute of Structural Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, 8093 Zurich, Switzerland; harmanci@ 123456ibk.baug.ethz.ch
                [2 ]Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, 8093 Zurich, Switzerland; utku.guelan@ 123456ifu.baug.ethz.ch (U.G.); holzner@ 123456ifu.baug.ethz.ch (M.H.)
                Author notes
                [* ]Correspondence: chatzi@ 123456ibk.baug.ethz.ch
                [†]

                This paper is an extended version of Harmanci, Y.E.; Gulan, U.; Holzner, M.; Chatzi, E. A Comparative Study on 2D and 3D Tracking of Vibration via Motion Magnified High-speed Videos. In Proceedings of the 7th World Conference on Structural Control and Monitoring, Qingdao, China, 22–25 July 2018.

                Author information
                https://orcid.org/0000-0002-6739-218X
                https://orcid.org/0000-0002-8639-6936
                https://orcid.org/0000-0003-2702-8612
                https://orcid.org/0000-0002-6870-240X
                Article
                sensors-19-01229
                10.3390/s19051229
                6427300
                30862051
                8618878f-aac0-4772-ab40-d23818108eb7
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 February 2019
                : 05 March 2019
                Categories
                Article

                Biomedical engineering
                vibration-based measurement,shm,structural identification,motion magnification,particle tracking velocimetry

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