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Mid-America Transportation Center

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


University

University of Kansas

Principal Investigator
William Collins
PI Contact Information
william.collins@ku.edu
Funding Source(s) and Amounts Provided
USDOT: $84,129
KU: $90,705
Total Project Cost
$ 174,834
Agency ID or Contract Number
69A3551747107
Start Date
11/27/2018
End Date
12/31/2019
Brief Description of Research Project
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.
Describe Implementation of Research Outcomes
Impacts/Benefits of Implementation
Web Links
Modal Orientation
  • Autonomous
  • Bridges
  • Systems