Automated Bridge Inspection Using Digital Image Correlation Phase I: Methodology Development

Details

• Creators:
  Collins, William ; Bennett, Caroline ; Li, Jian ; Sutley, Elaina ; Dellenbaugh, Landon ; Al-Salih, Hayder ; Juno, Mary
• Corporate Creators:
  University of Kansas. Dept. of Civil, Environmental and Architectural Engineering
• Corporate Contributors:
  University of Nebraska. Mid-America Transportation Center ; United States. Department of Transportation. Federal Highway Administration ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Automation Bridges Cracking Digital Displays Digital Image Correlation Fatigue (Mechanics) Inspection Methodology Steel
• Publication/ Report Number:
  25-1121-0005-151-1
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (December 2017- December 2018)
• Corporate Publisher:
  University of Nebraska. Mid-America Transportation Center
• Abstract:
  Distortion-induced fatigue cracks are a major concern in steel bridges built prior to the 1980s in the United States. Distortion induced fatigue cracks make up the majority of fatigue cracks in bridges, but Departments of Transportation have to primarily rely on the use of visual inspections to locate and characterize fatigue cracking, despite recent studies proving that visual inspections fail to consistently identify realistically sized fatigue cracks. Many fatigue crack detection methodologies have been proposed and examined, but the methods are dependent on detection equipment physically attached to the bridge, such as sensor networks. This limits the effectiveness and flexibility of the methods for sensing multiple fatigue susceptible regions. Developing an inspection technique that does not rely on human visual inspection or physical attachments has the potential to reduce the risk of injury to inspectors, increase reliability, and decrease the time and cost of performing inspections. Vision-based technologies are an active are of research working to develop alternatives to manual inspections of transportation infrastructure. While many vision-based technologies focus on macro-indicators of damage, digital image correlation (DIC) has shown promise for detecting and characterizing fatigue cracks. DIC measurements have the ability to capture full-field displacements and surface strains, allowing for the potential of identifying and characterizing both in-plane and out-of-plane fatigue cracks, such as those occurring on steel bridges exposed to loading through differential girder displacement. This paper describes an experimental study in which a methodology for crack detection was formulated using an in-plane test specimen and then tested on a scaled steel girder-to-cross frame specimen to evaluate the success of the method at detecting out-of-plane cracking. Preliminary results indicate that DIC is successful at locating cracks and determining the length of the crack.
• Format:
  PDF
• Funding:
  69A3551747107
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:9f6522ef4fbefef21bf92ba56e7b2e1a5c59f7ce64e8b0e6b103129d746e44afb2abc27d17e3cba949748be66d09b0eed4ac4223e8f9bfdf6ef18f018f1cbc35
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/74538/dot_74538_DS1.pdf
• File Type:
  [PDF - 16.45 MB ]