This work explores the application of Distributed Optical Fiber Sensing (DOFS) for structural health monitoring within the context of Building Information Modeling (BIM). The study addresses concerns about reliability and implementation of optical sensing techniques by providing, for the first time to the authors' knowledge, a technical validation of two DOFS technologies in a real framework. Strain measurements are carried out on a small reinforced concrete beam using Optical Frequency Domain Reflectometry (OFDR) and Brillouin Optical Frequency Domain Analysis (BOFDA). Both methods successfully detect induced strain, with OFDR demonstrating superior resolution (3 cm) and faster measurement times (under 30 s), but exhibiting noisy results and requiring post-processing filtering. On the other hand, BOFDA provides a 40 cm resolution and a 2-minute measurement time, but can measure over several km and has the potential for monitoring large infrastructures. A larger-scale experiment is then performed on a decommissioned bridge beam to simulate real infrastructure monitoring for BIM development. BOFDA provides consistent results and accurately predicts the location of failure during destructive testing. Although OFDR again shows higher resolution, its limited sensing range and installation constraints demonstrate that it is unsuitable for large structures. Ultimately, the study proves the potential of both DOFS techniques to replace extensive conventional sensor networks with single optical fibers, offering a unique benchmark for future applications in civil engineering. Ongoing data analysis promises further insights into sensor calibration and data interpretation.

Real-framework comparison of optical fiber distributed sensing techniques for Building Information Modeling / Olivero, Massimo; Rizzelli, Giuseppe; Bellezza Prinsi, Chiara; Pellegrini, Saverio; Quattrone, Antonino; Tondolo, Francesco; Sabia, Donato; Perrone, Guido; Gaudino, Roberto. - ELETTRONICO. - (2025), pp. 25-26. ( 2025 IMEKO TC2 International Symposium on Modern Photonic Metrology PhotoMet 2025 - Shaping the Future of Photonic Metrology Modena (Ita) 01 - 03 September 2025) [10.21014/tc2-2025.013].

Real-framework comparison of optical fiber distributed sensing techniques for Building Information Modeling

Olivero, Massimo;Rizzelli, Giuseppe;Bellezza Prinsi, Chiara;Pellegrini, Saverio;Quattrone, Antonino;Tondolo, Francesco;Sabia, Donato;Perrone, Guido;Gaudino, Roberto
2025

Abstract

This work explores the application of Distributed Optical Fiber Sensing (DOFS) for structural health monitoring within the context of Building Information Modeling (BIM). The study addresses concerns about reliability and implementation of optical sensing techniques by providing, for the first time to the authors' knowledge, a technical validation of two DOFS technologies in a real framework. Strain measurements are carried out on a small reinforced concrete beam using Optical Frequency Domain Reflectometry (OFDR) and Brillouin Optical Frequency Domain Analysis (BOFDA). Both methods successfully detect induced strain, with OFDR demonstrating superior resolution (3 cm) and faster measurement times (under 30 s), but exhibiting noisy results and requiring post-processing filtering. On the other hand, BOFDA provides a 40 cm resolution and a 2-minute measurement time, but can measure over several km and has the potential for monitoring large infrastructures. A larger-scale experiment is then performed on a decommissioned bridge beam to simulate real infrastructure monitoring for BIM development. BOFDA provides consistent results and accurately predicts the location of failure during destructive testing. Although OFDR again shows higher resolution, its limited sensing range and installation constraints demonstrate that it is unsuitable for large structures. Ultimately, the study proves the potential of both DOFS techniques to replace extensive conventional sensor networks with single optical fibers, offering a unique benchmark for future applications in civil engineering. Ongoing data analysis promises further insights into sensor calibration and data interpretation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3008100