Supporting quantitative structural assessment of highway bridges through the use of LiDAR scanning

Adriana Trias, Yi Yu, Jie Gong, Franklin L. Moon

Research output: Contribution to journalArticlepeer-review

Abstract

The use of laser scanning in the realm of bridge assessment has been primarily limited to measuring large bridge dimensions. Given the scale of these measurements compared to standard accuracy metrics for LiDAR sensors, it follows that they may be captured with relatively small errors (<1%). This paper explores LiDAR’s capacity to (a) estimate smaller cross-section dimensions of an operating bridge, and (b) quantify the observed errors in terms of capacity calculations (as opposed to simple percent errors). To satisfy these objectives, sixteen LiDAR scans of an eleven-span steel girder bridge were completed under normal operating conditions. Various dimensional quantities were extracted from the data both directly and using standard plane-fitting approaches (Plane Fitting, Ransac). Results indicated that dimensions obtained from Plane Fitting resulted in flexural capacities 4%-7% less than those computed using the dimensions from the bridge plans. The Ransac method estimated errors within 7%-10%, while the dimensions obtained directly from the point cloud data resulted in capacity errors of 9%-13%. Due to common errors sources, all dimensions were conservatively estimated throughout this study. However, the observed distortion of elements due to fabrication stresses, showed to have the potential of overestimation of dimensions if planar assumptions are made.

Original languageEnglish (US)
JournalStructure and Infrastructure Engineering
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Safety, Risk, Reliability and Quality
  • Geotechnical Engineering and Engineering Geology
  • Ocean Engineering
  • Mechanical Engineering

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