UAV Vision-Based Method for Multi-Point Displacement Measurement of Bridges

Area of Science:

• Civil Engineering
• Geomatics Engineering
• Structural Health Monitoring

Background:

• Vision-based bridge displacement measurement using Unmanned Aerial Vehicles (UAVs) faces challenges due to camera motion interference and performance limitations.
• Existing UAV motion correction methods lack the required precision for effective bridge monitoring.
• There is a need for high-performance cameras that can act as adaptive sensors for accurate structural monitoring.

Purpose of the Study:

• To propose a novel UAV vision-based method for multi-point displacement measurement of bridges.
• To develop an integrated monitoring system comprising a UAV-mounted camera, computing terminal, and targets.
• To evaluate the system's performance in monitoring dynamic bridge displacements under operational loads.

Main Methods:

• Development of a UAV vision-based technique for multi-point displacement measurement.
• Implementation of a monitoring system including a UAV, computing terminal, and targets.
• Field testing on the Lunzhou Highway Bridge to capture dynamic displacements under vehicle loads.

Main Results:

• The proposed system accurately measured vertical multi-point displacements across the entire span of the Lunzhou Highway Bridge.
• Monitoring results closely matched those obtained using a Scheimpflug camera.
• The system achieved a root mean square error (RMSE) of less than 0.3 mm.

Conclusions:

• The developed UAV vision-based method effectively addresses challenges in bridge displacement monitoring.
• The system provides essential, high-accuracy data for bridge safety assessments and structural health monitoring.
• The findings demonstrate the potential of UAVs as a viable tool for precise infrastructure monitoring.