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Effectiveness of Vibration-Based Techniques for Damage Localization and Lifetime Prediction in Structural Health Monitoring of Bridges: A Comprehensive Review

Auteur(s): ORCID
ORCID
ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 4, v. 14
Page(s): 1183
DOI: 10.3390/buildings14041183
Abstrait:

Bridges are essential to infrastructure and transportation networks, but face challenges from heavier traffic, higher speeds, and modifications like busway integration, leading to potential overloading and costly maintenance. Structural Health Monitoring (SHM) plays a crucial role in assessing bridge conditions and predicting failures to maintain structural integrity. Vibration-based condition monitoring employs non-destructive, in situ sensing and analysis of system dynamics across time, frequency, or modal domains. This method detects changes indicative of damage or deterioration, offering a proactive approach to maintenance in civil engineering. Such monitoring systems hold promise for optimizing the management and upkeep of modern infrastructure, potentially reducing operational costs. This paper aims to assist newcomers, practitioners, and researchers in navigating various methodologies for damage identification using sensor data from real structures. It offers a comprehensive review of prevalent anomaly detection approaches, spanning from traditional techniques to cutting-edge methods. Additionally, it addresses challenges inherent in Vibration-Based Damage (VBD) SHM applications, including establishing damage thresholds, corrosion detection, and sensor drift.

Copyright: © 2024 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10773671
  • Publié(e) le:
    29.04.2024
  • Modifié(e) le:
    05.06.2024
 
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