Develop a UAV Platform for Automated Bridge Inspection

Inspecting the health of bridges is important to maintain the operation of a road network while protecting public users’ safety. However, routinely inspecting numerous bridges in a state over a long time period by human is a labor-intense and costly task, or a dangerous task in some environments such as inspecting the underneath of a bridge spanning across a rushing river. This project seeks to develop an automated bridge inspection technology that can make the inspection process safer, more efficient and convenient. The focus of this research is to study the technical foundation of an Unmanned Aerial Vehicle (UAV) system capable of remotely inspecting bridges with sensors without interfering with road operation. The applicability of this technique will be validated by a prototype UAV system with field testing.

• Record URL:
  https://matc.unl.edu/assets/documents/matcfinal/Yin_DevelopaUAVPlatformforAutomatedBridgeInspection.pdf
• 
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Missouri University of Science and Technology, Rolla

  Department of Computer Science
  Rolla, MO  United States 

  Mid-America Transportation Center

  University of Nebraska-Lincoln
  2200 Vine Street, PO Box 830851
  Lincoln, NE  United States  68583-0851

  Research and Innovative Technology Administration

  University Transportation Centers Program
  Washington, DC  United States  20590
• Authors:
  • Yin, Zhaozheng
  • Mao, Yunxiang
  • Seto, Chris
• Publication Date: 2015-3

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Photos; References;
• Pagination: 26p

Subject/Index Terms

• TRT Terms: Bridges; Drones; Field tests; Inspection; Prototypes; Remote sensing; Structural health monitoring; Validation
• Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01675634
• Record Type: Publication
• Report/Paper Numbers: MATC-MS&T: 295, 25-1121-0003-295
• Files: UTC, TRIS, ATRI, USDOT
• Created Date: Jul 20 2018 3:47PM