Automated Bridge Inspection using Digital Image Correlation and other Vision-based Methods

Building on the work previously performed as part of this study, the methods developed for fatigue crack characterization using digital image correlation (DIC) will be applied to full-scale structures prone to both fatigue and fracture failures. This will include full-scale sign structure components experiencing fatigue loading and subsequent cracking, as well as representative large-scale girder specimens prone to constraint-induced fracture failure. Additionally, optical data will be generated and collected to use in evaluating the potential for machine learning and artificial intelligence methods in fatigue crack identification and characterization. This phase of the project represents deployment of the previously-developed methodologies while still looking forward to other enhanced vision-based tools. Deployment mechanisms will include various hand-held and stationary cameras, unmanned aerial vehicles (UAVs), and/or augmented reality devices such as the Microsoft HoloLens2. It is anticipated this research program will lead to vision-based inspection tools that can potentially be used in automated bridge inspections.

Language

• English

Project

• Status: Active
• Funding: $399371
• Contract Numbers:

  69A3551747107

• 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:

  Mid-America Transportation Center

  University of Nebraska-Lincoln
  2200 Vine Street, PO Box 830851
  Lincoln, NE  United States  68583-0851
• Performing Organizations:

  University of Kansas, Lawrence

  1530 West 15th Street
  Lawrence, KS  United States  66045
• Principal Investigators:

  Collins, William N.

  Bennett, Caroline

• Start Date: 20230213
• Expected Completion Date: 20240630
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Bridges; Fatigue cracking; Fracture tests; Image analysis; Inspection; Machine learning
• Identifier Terms: Automated Inspection of Structural Components
• Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01908346
• Record Type: Research project
• Source Agency: Mid-America Transportation Center
• Contract Numbers: 69A3551747107
• Files: UTC, RIP
• Created Date: Feb 17 2024 4:13PM