Beam Damage Detection and Characterization Using Rotation Response from a Moving Load and Damage Candidate Grid Search (DCGS)

Structural health monitoring (SHM) increasingly contributes to the safety and durability of key infrastructure, especially bridges. This research introduces a rotation-based approach for damage detection and quantification using a damage candidate grid search technique (DCGS) on simply supported girder bridges under quasi-static or slowly moving loading conditions. Applying the principle of virtual work, the healthy and candidate-damaged rotation responses are analytically obtained and compared with the rotation observed directly at the moving load location. Damage is defined in terms of three key parameters: the start and the end of the damage, L1 and L2, respectively, and the damage severity β. The DCGS method is validated using finite element model simulations of 12 damage scenarios subjected to different noise levels. A statistical analysis and confidence interval characterize the accuracy and consistency of the top ten estimations produced by the DCGS method. A damage length ratio (DLR), defined from the span of the beam, L, and the damage location, L1 and L2, improves the robustness of the methodology against measurement noise by reducing possible false positive estimations. Additionally, the experimental results on two beam structures further validate the method. Absolute relative errors (AREs) of about 6% and absolute errors (AEs) of around 0.16 between the estimated and real damage parameters characterize the performance of the technique, considering damage location and damage severity, respectively. The results show that the DCGS methodology can effectively locate damage and estimate its severity in the presence of noise. The developed framework provides a sensitive and practical SHM tool that is suitable for early damage detection in railway and road bridges.

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Publication Details

Journal
Applied Sciences
Published
2026-01-05
DOI
https://doi.org/10.3390/app16010539
Primary Topic
Structural Health Monitoring Techniques
Type
article
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article

Beam Damage Detection and Characterization Using Rotation Response from a Moving Load and Damage Candidate Grid Search (DCGS)

Muath Y. Alhumaidi, Brett Story
Applied Sciences
Structural Health Monitoring Techniques
article

Beam Damage Detection and Characterization Using Rotation Response from a Moving Load and Damage Candidate Grid Search (DCGS)

Muath Y. Alhumaidi, Brett Story
article en

Abstract

Structural health monitoring (SHM) increasingly contributes to the safety and durability of key infrastructure, especially bridges. This research introduces a rotation-based approach for damage detection and quantification using a damage candidate grid search technique (DCGS) on simply supported girder bridges under quasi-static or slowly moving loading conditions. Applying the principle of virtual work, the healthy and candidate-damaged rotation responses are analytically obtained and compared with the rotation observed directly at the moving load location. Damage is defined in terms of three key parameters: the start and the end of the damage, L1 and L2, respectively, and the damage severity β. The DCGS method is validated using finite element model simulations of 12 damage scenarios subjected to different noise levels. A statistical analysis and confidence interval characterize the accuracy and consistency of the top ten estimations produced by the DCGS method. A damage length ratio (DLR), defined from the span of the beam, L, and the damage location, L1 and L2, improves the robustness of the methodology against measurement noise by reducing possible false positive estimations. Additionally, the experimental results on two beam structures further validate the method. Absolute relative errors (AREs) of about 6% and absolute errors (AEs) of around 0.16 between the estimated and real damage parameters characterize the performance of the technique, considering damage location and damage severity, respectively. The results show that the DCGS methodology can effectively locate damage and estimate its severity in the presence of noise. The developed framework provides a sensitive and practical SHM tool that is suitable for early damage detection in railway and road bridges.

Applied SciencesVol. 16(1)
Southern Methodist University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 97%
Structural Health Monitoring Techniques
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