dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
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Universitat Politècnica de Catalunya. EC - Enginyeria de la Construcció
dc.contributor.author
Komarizadehasl, Seyedmilad
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González Jiménez, Manuel Antonio
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Pérez Casas, José María
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Lozano Galant, José Antonio
dc.contributor.author
Turmo Coderque, José
dc.identifier
Komarizadehasl, S. [et al.]. Eigenfrequency analysis using fiber optic sensors and low-cost accelerometers for structural damage detection. "Engineering structures", Novembre 2024, vol. 318, núm. article 118684.
dc.identifier
https://hdl.handle.net/2117/414187
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10.1016/j.engstruct.2024.118684
dc.description.abstract
Structural Health Monitoring (SHM) is crucial for infrastructure safety and integrity. Arduino-based sensors are gaining popularity in low-cost SHM structures. Distributed fiber optic systems (DFOS), such as Distributed Acoustic Sensing (DAS), are employed for accurate SHM despite their high costs, computational demands, and energy consumption. The primary objectives of this work are to compare the accuracy of an accelerometer named LARA (Low-cost Adaptable Reliable Accelerometer (LARA)) that utilizes both Arduino and Raspberry Pi technologies with a DAS system in detecting structural damage and to explore the potential advantages of combining LARA and DAS to create an effective SHM tool. This study is the first to enhance the design of LARA. Subsequently, LARA and DAS were used in a laboratory setting to analyze eigenfrequency changes in a beam model with induced localized damage. Finally, this study evaluated the precision and reliability of LARA and its potential role as a trigger for DAS in detecting localized damage. The findings show that both LARA and DAS can identify changes in the eigenfrequencies of damaged structures with deviations as small as 3.68 %. Consequently, LARA demonstrated its potential as a trigger for DAS, significantly reducing the computational demands while enriching the analysis. This approach offers highly accurate eigenfrequency measurements and enhances the analytical capabilities of DAS by identifying the primary axes of the detected eigenfrequencies.
dc.description.abstract
The authors are indebted to the projects PID2021-126405OB-C31 and PID2021–126405OB-C32 funded by FEDER funds A way to make Europe and Spanish Ministry of Economy and Competitiveness MICIN/AEI/10.13039/501100011033/. Dr. Seyedmilad Komarizadehasl is indebted to a grant provided by the Polytechnic University of Catalonia to encourage research among new teaching staff with a reference of ALECTORS-2023.
dc.description.abstract
Peer Reviewed
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Postprint (author's final draft)
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application/pdf
dc.relation
https://www.sciencedirect.com/science/article/abs/pii/S014102962401246X
dc.relation
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126405OB-C31/ES/DESARROLLO DE SENSORES MODULARES DE BAJO COSTE PARA SU USO EN IDENTIFICACION ESTRUCTURAL DE PUENTES SOMETIDOS A CARGAS QUASIESTATICAS/
dc.relation
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126405OB-C32/ES/SISTEMA DE ALARMA PARA SISTEMAS DE GESTION DE PUENTES CON GEMELOS DIGITALES BIM UTILIZANDO INTELIGENCIA ARTIFICIAL/
dc.rights
http://creativecommons.org/licenses/by-nc-nd/4.0/
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Restricted access - publisher's policy
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Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
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Structural health monitoring
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Low-cost safety control
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Distributed fiber optic sensors
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Eigenfrequency analysis
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Structural safety monitoring
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Low-cost sensors
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Monitorització de la salut estructural
dc.title
Eigenfrequency analysis using fiber optic sensors and low-cost accelerometers for structural damage detection