Inverse Problem Approaches for Bridge Structural Health Monitoring Using Displacement Data

Marin-Artieda, Claudia

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Inverse Problem Approaches for Bridge Structural Health Monitoring Using Displacement Data

2026-08-01
By Marin-Artieda, Claudia

File Language:

English

Details

Creators:

Marin-Artieda, Claudia
Corporate Creators:

Howard University. Department of Civil Engineering ; Morgan State University.Safety and Mobility Advancement Regional Transportation and Economics Research Center (SMARTER) University Transportation Center (UTC)
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:

Asset Management Benchmarks Bridge Management Systems Cameras Computer Vision Damage Localization Displacement Measurement Finite Element Method Inverse Problems Laboratory Studies Laboratory Tests Literature Reviews Measurement Modal Strain Energy Structural Health Monitoring
Publication/ Report Number:

SM19
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report: May 2025 to May 2026
Corporate Publisher:

Morgan State University.Safety and Mobility Advancement Regional Transportation and Economics Research Center (SMARTER) University Transportation Center (UTC)
Abstract:

This project developed and validated an inverse problem framework for truss bridges that uses displacement as the primary diagnostic input. Displacement histories are extracted from single-camera video by optical flow tracking, modal parameters are identified by output-only methods with bootstrap uncertainty quantification, and element-level damage indices are formed from the resulting mode shapes. The framework was demonstrated through three progressive laboratory studies: global stiffness identification from a single tracked joint on a spring-mounted Warren truss; element-level localization on a fourteen-bay benchmark truss using finite-element response with synthetic noise; and element-level localization on the same benchmark truss using video-derived displacement. Both video cases identified the damaged member at rank one within the correct bay. Localization is reliable at stiffness reductions of thirty percent and above. At lower severities, identification remains confined to the correct bay although the individual member is not consistently ranked first. Severity is reported as a normalized indicator score rather than a calibrated stiffness loss, and calibration of that mapping is identified as the principal remaining step.
Format:

PDF
Funding:

69A3552348303
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:7eda557408e8b75b62d3fc6dc55fc3ee45ecddb7221fb9d252d2d07228e910f346c32efc5b79147904f696d7b9216aad3bbde0aba3930b54e5ed37c178e23459
Download URL:

https://rosap.ntl.bts.gov/view/dot/93085/dot_93085_DS1.pdf
File Type:

[PDF - 3.56 MB ]

File Language:

English

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