PSI - Issue 44

Available online at www.sciencedirect.com Structural Integrity Procedia 00 (2022) 000 – 000 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2022) 000 – 000 ScienceDirect

www.elsevier.com/locate/procedia

www.elsevier.com/locate/procedia

ScienceDirect

Procedia Structural Integrity 44 (2023) 1602–1607

© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the XIX ANIDIS Conference, Seismic Engineering in Italy. © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license ( https://creativecommons.org/licenses/by-nc-nd/4.0 ) Peer-review under responsibility of the scientific committee of the XIX ANIDIS Conference, Seismic Engineering in Italy bstract Ageing structures and infrastructures need to be monit red to assess their structural health conditions and prioritiz interventions t possibly extend their service life. T d this, acceler meters and velocimeters are routinely ad pted and ar part of a consolidated state-of-the-art proc dure. Nonethel ss, some difficulties may arise in field applications, related to energy supply, cost, and accessibility of the devices. M reover, the position of the sensors needs to be decided a priori, with some degree of engineering judgment. Alternative techniques based on computer vision have emerged in the la t decade and are becoming mor and more popular s they allow to overcome most f the limitations reported above. The main adv ntages of these a proaches rely on the possibility of hi h-density measurements nd a relatively sim le acquisition process, for which either an expensive equipm nt nor a vanc d technical skills are ma dat rily required. In this paper, a computer vision-bas d technique is presented, which combines motion mag ification and statistical al orithms. It was applied to extract the atural frequencies of reinforced concrete elevat d water tank, vibrating under environmental noise excitation. To this ai , ev ral ideos were recorded with a comm rcial refl x ca era and post-processed selecting a repre entative area, by tracking in time either the vari tion of the intensity or t e motion of a selected number of pixels. Computer vision-based outcomes were validated against the results provided by accelerometers to discuss advantages and limitations of the proposed dynamic identification approach and identify future research challenges in this field. © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license ( https://creativecommons.org/licenses/by-nc-nd/4.0 ) Peer-review under responsibility of the scientific committee of the XIX ANIDIS Conference, Seismic Engineering in Italy Abstract Ageing structures and infrastructures need to be monitored to assess their structural health conditions and prioritize interventions to possibly extend their service life. To do this, accelerometers and velocimeters are routinely adopted and are part of a consolidated state-of-the-art procedure. Nonetheless, some difficulties may arise in field applications, related to energy supply, cost, and accessibility of the devices. Moreover, the position of the sensors needs to be decided a priori, with some degree of engineering judgment. Alternative techniques based on computer vision have emerged in the last decade and are becoming more and more popular as they allow to overcome most of the limitations reported above. The main advantages of these approaches rely on the possibility of high-density measurements and a relatively simple acquisition process, for which neither an expensive equipment nor advanced technical skills are mandatorily required. In this paper, a computer vision-based technique is presented, which combines motion magnification and statistical algorithms. It was applied to extract the natural frequencies of a reinforced concrete elevated water tank, vibrating under environmental noise excitation. To this aim, several videos were recorded with a commercial reflex camera and post-processed selecting a representative area, by tracking in time either the variation of the intensity or the motion of a selected number of pixels. Computer vision-based outcomes were validated against the results provided by accelerometers to discuss advantages and limitations of the proposed dynamic identification approach and identify future research challenges in this field. XIX ANIDIS Conference, Seismic Engineering in Italy Dynamic identification of an elevated water tank through digital video processing Marialuigia Sangirardi a,b *, Stefano De Santis b , Vittorio Altomare b , Vincenzo Giannetto c , XIX ANIDIS Conference, Seismic Engineering in Italy Dynamic identification of an elevated water tank through digital video processing Marialuigia Sangirardi a,b *, Stefano De Santis b , Vittorio Altomare b , Vincenzo Giannetto c , Pietro Meriggi b , Marika Volpe c , Gianmarco de Felice b a University of Oxford, Department of Engineering Science, Parks Road, OX1 3PJ Oxford (UK). b Università degli Studi Roma Tre, Dipartimento di Ingegneria, Via Vito Volterra 62, 00146 Roma (Italy). c Indagini Strutturali srl, Via Guido de Ruggiero 5, 00142 Roma (Italy). Pietr Meriggi b , Marika Volpe c , Gi nmarco de Felice b a University of Oxford, Department of Engineering Scienc , Parks Road, OX1 3PJ Oxford (UK). b Università degli Studi Roma Tre, Dipartimento di Ingegneria, Via Vito Volterra 62, 00146 Roma (Italy). c Indagini Strutturali srl, Via Guido de Ruggiero 5, 00142 Roma (Italy).

Keywords: Structural health monitoring; computer-vision-based; motion magnification; natural frequency.

Keywords: Structural health monitoring; computer-vision-based; motion magnification; natural frequency.

2452-3216 © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the XIX ANIDIS Conference, Seismic Engineering in Italy 2452-3216 © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the XIX ANIDIS Conference, Seismic Engineering in Italy

2452-3216 © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the XIX ANIDIS Conference, Seismic Engineering in Italy. 10.1016/j.prostr.2023.01.205