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LiDAR-Based Bridge Displacement Estimation Using 3D Spatial Optimization.

Gichun Cha1, Sung-Han Sim1, Seunghee Park1

  • 1School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University, Suwon 16419, Korea.

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|December 16, 2020
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Summary
This summary is machine-generated.

This study introduces a non-contact method using light detection and ranging (LiDAR) to estimate vertical displacement in large civil engineering structures. The technique utilizes octree partitioning for accurate structural health monitoring and safety evaluation.

Keywords:
deflectionlight detection and ranging (LiDAR)octree space partitioning (OSP)structural health monitoring (SHM)terrestrial laser scanning (TLS)

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Area of Science:

  • Civil Engineering
  • Geospatial Technology
  • Structural Health Monitoring

Background:

  • Increasing scale of civil engineering structures necessitates advanced non-contact inspection methods for safety evaluation.
  • Environmental exposure and long-term loading can compromise structural integrity and original function.
  • Existing methods may be limited in assessing overall shape, size, and dynamic displacement.

Discussion:

  • A novel method is proposed for estimating vertical displacement using light detection and ranging (LiDAR) technology.
  • Laser-scanned point cloud data is processed in a 3D space using an octree partitioning technique.
  • Vertical displacement is calculated by identifying nodes within the octree structure that indicate deformation.

Key Insights:

  • The proposed LiDAR-based method enables accurate, non-contact measurement of vertical displacement in structures.
  • Octree space partitioning effectively organizes 3D point cloud data for deformation analysis.
  • Static loading experiments validated the performance of the displacement estimation technique.

Outlook:

  • The developed technique shows significant potential for real-time structural health monitoring (SHM) applications.
  • Integration with existing SHM systems can enhance the safety and longevity of civil infrastructure.
  • Further research could explore dynamic displacement monitoring and predictive maintenance using this approach.