Raspberry shake-based rapid structural identification of existing buildings subject to earthquake ground motion: the case study of Bucharest

Ali Güney Özcebe, Alexandru Tiganescu*, Ekin Ozer, Caterina Negulescu, Juan Jose Galiana-merino, Enrico Tubaldi, Dragos Toma-danila, Sergio Molina, Alireza Kharazian, Francesca Bozzoni, Barbara Borzi, Stefan Florin Balan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
18 Downloads (Pure)

Abstract

The Internet of things concept empowered by low-cost sensor technologies and headless computers has upscaled the applicability of vibration monitoring systems in recent years. Raspberry Shake devices are among those systems, constituting a crowdsourcing framework and forming a worldwide seismic network of over a thousand nodes. While Raspberry Shake devices have been proven to densify seismograph arrays efficiently, their potential for structural health monitoring (SHM) is still unknown and is open to discovery. This paper presents recent findings from existing buildings located in Bucharest (Romania) equipped with Raspberry Shake 4D (RS4D) devices, whose signal recorded under multiple seismic events has been analyzed using different modal identification algorithms. The obtained results show that RS4D modules can capture the building vibration behavior despite the short-duration and low-amplitude excitation sources. Based on 15 RS4D device readings from five different multistorey buildings, the results do not indicate damage in terms of modal frequency decay. The findings of this research propose a baseline for future seismic events that can track the changes in vibration characteristics as a consequence of future strong earth-quakes. In summary, this research presents multi-device, multi-testbed, and multi-algorithm evidence on the feasibility of RS4D modules as SHM instruments, which are yet to be explored in earthquake engineering.

Original languageEnglish
Article number4787
Number of pages24
JournalSensors
Volume22
Issue number13
Early online date24 Jun 2022
DOIs
Publication statusPublished - 24 Jun 2022

Funding

Funding: This work is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821046, project TURNkey (Towards more Earthquake‐resil‐ ient Urban Societies through a Multi‐sensor‐based Information System enabling Earthquake Fore‐ casting, Early Warning and Rapid Response actions).

Keywords

  • modal identification
  • rapid response to earthquakes (RRE)
  • Raspberry Shake 4D
  • TURNkey project
  • vibration-based structural health monitoring

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