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May 13, 2026InfrastructuresOpen Access

Comparative Study of Modal Curvature and AI-Based Approaches for Vibration-Based Damage Detection in Structural Health Monitoring Systems of Prestressed Concrete Beams

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Authors

ABAntonio BilottaAPAndrea PollastroICIvan Di Cristinzi

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Overview

Comparative study shows vibration-based damage detection in prestressed concrete beams reveals anomalies efficiently, highlighting AI's potential.

Key Points

  • To compare modal curvature and AI-based approaches for damage detection in structural health monitoring of prestressed concrete beams.
  • Utilized operational modal analysis for vibration-based detection.
  • Implemented machine learning techniques for anomaly detection and defect localization.
  • Compared effectiveness of modal parameters and AI-based systems using acceleration measurements.
  • Both methods can effectively detect damage, with challenges in identifying defects using dynamic responses.
  • AI-based approach allows earlier alarms with fewer sensors compared to modal curvature methods.
  • Modal curvature offers better anomaly explanation but requires more sensors for effective monitoring.

Cite This Study

Bilotta et al. (2026) studied this question.

synapsesocial.com/papers/6a03cb781c527af8f1ecf1c5https://doi.org/10.3390/infrastructures11050164
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Vibration and Modal Analysis for Damage Detection in Cantilever Beams: Assessing Presence, Location, and Severity Through Numerical and Experimental Approaches2025 · 1 citations
  2. 2Safety Assessment Method for Engineering Structures Based on Modal Curvature2026
  3. 3ML Based Damage Detection in Simply Supported Beams Using Free Vibration Data2024 · 1 citations
  4. 4Damage Detection on Steel Truss Bridges Using Modal Based Methods2026
  5. 5Modal identification of prestressed concrete beams with artificial damage on prestressing strands2026