Automated Bridge Inspection using Digital Image Correlation Phase III – Examination Alternative Vision-based Methods and Deployment Mechanisms for Field Implementation
Building on the previous years of this study, the methods developed for fatigue crack characterization using digital image correlation (DIC) will be examined using open-source software and off-the-shelf hardware components. Previous development and analysis of the DIC-based crack inspection methodology relied on a commercial package of hardware and software. Results indicate that hardware setup, system calibration, and environmental conditions greatly influence the reliability of the methodology. Open-source solutions may allow for more flexibility and customization of the system, potentially allowing for a more reliable and robust application of the developed crack characterization methodology. Open-source software will be identified and evaluated with existing data sets. Additionally, alternative vision-based inspection tools will also be investigated. As vision-based technology is rapidly advancing, potential for application to infrastructure inspection should be evaluated. Comparisons will be made with the existing DIC-based protocol to determine whether alternative tools are currently feasible for fatigue crack identification and characterization. Finally, deployment mechanisms will be identified and investigated. This includes commercially-available and research-focused tools such as unmanned aerial vehicles (UAVs) and robotic crawlers. This research program is anticipated to lead to implementation of a vision-based inspection tool for use in automated bridge inspections.
Language
- English
Project
- Status: Completed
- Funding: $156394
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Contract Numbers:
69A3551747107
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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 -
Project Managers:
Stearns, Amy
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Performing Organizations:
University of Kansas, Lawrence
2600 Learned Hall
Lawrence, KS United States 66045 -
Principal Investigators:
Collins, William
- Start Date: 20200624
- Expected Completion Date: 20210630
- Actual Completion Date: 20230630
- USDOT Program: University Transportation Centers Program
- Source Data: RiP Project 91994-68
Subject/Index Terms
- TRT Terms: Alternatives analysis; Automation; Bridges; Drones; Fatigue cracking; Image analysis; Implementation; Inspection; Machine vision; Methodology; Robots; Software
- Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation;
Filing Info
- Accession Number: 01752958
- Record Type: Research project
- Source Agency: Mid-America Transportation Center
- Contract Numbers: 69A3551747107
- Files: UTC, RIP
- Created Date: Sep 25 2020 2:55PM