Structural Health Monitoring (SHM) plays a vital role in maintaining the integrity of structures by providing continuous information about damage or anomalies. Vibration-based SHM, which focuses on the dynamic behavior of structures, offers insights into structural conditions through changes in dynamic properties. Among SHM approaches, damage localization is crucial for pinpointing the geometric location of damage. This paper proposes a method for damage localization using Short Time Fourier Transform and a Statistical Interpolation Damage Index. The proposed methodology is applied to a numerical case study involving a finite element beam model and to the S101 benchmark bridge, in Austria, demonstrating its efficacy in damage localization. The study also introduces a multi-level clustering approach to perform damage localization using smart decentralized sensor networks, able to reduce the volume of transmitted data and thereby the energy requirements. Results show promising outcomes in accurately identifying damage locations while minimizing data transmission.

Structural health monitoring of civil infrastructures using smart sensor networks

Giordano, Pier Francesco;Limongelli, Maria Pina
2024-01-01

Abstract

Structural Health Monitoring (SHM) plays a vital role in maintaining the integrity of structures by providing continuous information about damage or anomalies. Vibration-based SHM, which focuses on the dynamic behavior of structures, offers insights into structural conditions through changes in dynamic properties. Among SHM approaches, damage localization is crucial for pinpointing the geometric location of damage. This paper proposes a method for damage localization using Short Time Fourier Transform and a Statistical Interpolation Damage Index. The proposed methodology is applied to a numerical case study involving a finite element beam model and to the S101 benchmark bridge, in Austria, demonstrating its efficacy in damage localization. The study also introduces a multi-level clustering approach to perform damage localization using smart decentralized sensor networks, able to reduce the volume of transmitted data and thereby the energy requirements. Results show promising outcomes in accurately identifying damage locations while minimizing data transmission.
2024
Proceedings of SPIE - The International Society for Optical Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1267466
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