Traffic Disruption-Free Bridge Inspection Initiative with Robotic Systems [Research Summary]

Details

• Creators:
  Chen, Genda ; Harper, Jennifer
• Corporate Creators:
  Missouri University of Science and Technology
• Corporate Contributors:
  Missouri. Department of Transportation. Construction and Materials Division
• Subject/TRT Terms:
  • Bridge management systems
  • Inspection
  • Robotics
  • Remote sensing
  • Nondestructive tests
  • Machine learning
  • Artificial intelligence
  • Reconstruction
  • Quantitative analysis
  • Evaluation
  More +
• Publication/ Report Number:
  TR202004/TPF-5(395)
• Resource Type:
  Brief
• Geographical Coverage:
  United States ; Missouri
• Edition:
  Research Summary
• Corporate Publisher:
  Missouri. Department of Transportation. Construction and Materials Division
• Abstract:
  The research team evaluated 59 bridges in diverse types, age groups, and geographical locations. Best practices of the technologies were developed and summarized in inspection protocols and guidelines using commercial drones, structural crawlers, and hybrid uncrewed vehicles. Bridge inspection protocols and guidelines are presented in three parts: pre-inspection preparation, during-inspection execution, and post-inspection processing. The type and number of defects observed from the 59 selected bridges in three age groups (15-20, 25-30, and 35-40 years) are limited. Observed deterioration and damage include concrete cracks, concrete spalling, concrete delamination, rebar exposure, and steel corrosion.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/86978/dot_86978_DS1.pdf
• File Type:
  [PDF - 341.03 KB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:2cd9aed6383b157975aebf37e43dd1fa52cae8ff5f9cd70bdca0df24b94977a26919fee92aa7f7c3a341cf007bf3a5af9430e4fc8c3db9a440d63dee0d3f7313