Automated Bridge Inspection using Digital Image Correlation Phase II – Application of Digital Image Correlation Techniques for In-Service Inspection Conditions

An experimental study will be undertaken in which a series of steel compact specimens (C(T)) and steel bridge girder components will be tested in the KU Structural Engineering Laboratory. Specimens will be loaded cyclically to introduce and propagate fatigue cracks, and a digital image correlation (DIC) will be used to develop capabilities for detecting and monitoring fatigue cracking. Building on the previous research project, the current study will examine the capabilities of the DIC system and methodology under in-service inspection conditions. Variable amplitude loading will be applied to simulate ambient traffic conditions, while paint patterns for the DIC will be altered to replicate environmental changes to the material surface. The previously developed crack identification methodology will be modified as necessary for application under in-service conditions, working towards the development of an automated crack identification methodology. This research program is anticipated to lead to implementation of DIC for automated bridge inspections as part of robotic bridge inspection systems in future projects related to automated crack inspection.

• Record URL:
  http://matc.unl.edu/research/research_project.php?researchID=570

Language

• English

Project

• Status: Completed
• Funding: $174834
• 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

  Mid-America Transportation Center

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

  Mid-America Transportation Center

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

  Stearns, Amy

• Performing Organizations:

  University of Kansas, Lawrence

  Department of Civil Engineering, 2006 Learned Hall
  Lawrence, KS  United States  66045-2225
• Principal Investigators:

  Bennett, Caroline

  Li, Jian

  Collins, William

  Sutley, Elaina

• Start Date: 20181127
• Expected Completion Date: 20181204
• Actual Completion Date: 20191231
• USDOT Program: University Transportation Centers Program
• Source Data: 91994-37

Subject/Index Terms

• TRT Terms: Automation; Detection and identification technologies; Fatigue cracking; Girders; Image analysis; Inspection; Methodology; Steel bridges
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01693004
• Record Type: Research project
• Source Agency: Mid-America Transportation Center
• Contract Numbers: 69A3551747107
• Files: UTC, RIP
• Created Date: Feb 18 2019 7:55PM