Camera Based Computer Vision Measurements for Bridge Field Testing

When an inspection indicates significant damage or when higher loads are expected for a bridge, a load rating is performed, which can be done through analysis or field testing. Despite several advantages of bridge load rating using field testing data, it is not a common practice for the evaluation of bridge performance due to the cost of field operations and instrumentation. One way to reduce such costs is to utilize new technologies such as drones, computer vision, and digital image correlation (DIC). The main goal of this proposal is to develop frameworks and necessary tools to field test bridges using computer vision including either a ground-DIC system and/or drone-DIC system. Instead of using conventional sensors and data acquisition equipment, a few cameras, or a fleet of drones each equipped with a camera system will be deployed to measure bridge responses. To achieve the project goals, the most recent DIC technologies will be reviewed, current commercial and research products suitable for bridge response measurements will be evaluated, low-cost DIC tools and practical frameworks for bridge field testing will be developed, and a few bridges will be load tested using DIC and conventional sensors to validate and further refine the tools.

Language

  • English

Project

  • Status: Active
  • Funding: $437999
  • Contract Numbers:

    69A3552348308

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Center for Transformative Infrastructure Preservation and Sustainability

    North Dakota State University
    Fargo, ND  United States  58108
  • Project Managers:

    Tolliver, Denver

  • Performing Organizations:

    South Dakota State University

    Civil & Environmental Engineering
    Brookings, SD  United States 
  • Principal Investigators:

    Tazarv, Mostafa

    Won, Kwanghee

  • Start Date: 20240617
  • Expected Completion Date: 20260616
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program
  • Source Data: CTIPS-018

Subject/Index Terms

Filing Info

  • Accession Number: 01923669
  • Record Type: Research project
  • Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
  • Contract Numbers: 69A3552348308
  • Files: UTC, RIP
  • Created Date: Jul 8 2024 8:13AM