Development of an Automated Bridge Inspection Methodology using Digital Image Correlation - Phase I

University

University of Kansas

Principal Investigator

William Collins (william.collins@ku.edu)

Total Project Cost

$171,422

Funding Type

2016 USDOT

Start Date

12/5/2016

End Date

12/31/2018

Agency ID or Contract Number

69A3551747107

Abstract

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. The limits of the DIC system will be examined with respect to crack orientation (in-plane and out-of-plane), crack size (length and opening), and system proximity and orientation to the specimen. These results will be used to determine thresholds of applicability for use in automated bridge inspection. Examination of DIC output with respect to crack initiation and propagation will be used to develop 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.

Deliverables

Download the Final Report

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

Phase III: Automated Bridge Inspection Using Digital Image Correlation Part III: Examination Alternative Vision-Based Methods and Deployment Mechanisms for Field Implementation

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