Structure and Infrastructure Engineering· 2026Q1
Multi-source structural identification of undocumented historic bridges via 360°photogrammetry, operational modal analysis, and model updating
- 0citations
- Q1SCImago
- 2026year
Short summary
A new framework uses 360° photogrammetry and vibration testing to create accurate structural models of undocumented historic bridges, achieving <5% frequency error and MAC >0.90.
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Key points
- A novel framework combines 360° photogrammetry and ambient vibration testing for structural identification.
- The method is designed for undocumented and hard-to-reach historic bridges with limited data.
- A two-stage finite element model updating procedure refines boundary conditions and calibrates material parameters.
- Applied to Puente del Tranvía, the updated model showed <5% frequency error and MAC >0.90 compared to experimental modes.
AI-generated from the title and abstract; the full text is not read.
Abstract
This paper presents a robust, ultra-low-cost, and fully non-invasive framework for the structural identification of undocumented and hard-to-reach historic bridges under severe data-scarcity conditions. The proposed methodology combines: (i) tethered spherical (360°) photogrammetry for metrically reliable geometric reconstruction, (ii) Ambient Vibration Testing (AVT) for experimental dynamic identification, and (iii) a two-stage finite element model updating procedure encompassing expert-guided boundary-condition refinement followed by automated material parameter calibration. The workflow is demonstrated on the Puente del Tranvía (Pinos Puente, Granada, Spain), a riveted metallic truss bridge lacking archival documentation and affected by severe accessibility constraints. Starting exclusively from data acquired through a rope-suspended 360° camera, the proposed workflow enables the generation of detailed geometric blueprints and a mechanically consistent calibrated FE model. The updated model achieves frequency discrepancies below 5% and Modal Assurance Criterion (MAC) values exceeding 0.90 with respect to the experimentally identified modes. The results demonstrate that the proposed approach can significantly enhance the structural knowledge level of inaccessible bridges while minimising inspection costs, operational complexity, and human exposure risks.
The authors' abstract, as published at the source. Structure and Infrastructure Engineering, 2026 · DOI ↗
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