摘要: |
This project aims to develop the quality assurance (QA) and quality control (QC)
guidelines for robot-based bridge inspection. These QA/QC guidelines are developed to
ensure good quality of multimodal sensor data for the inspection of bridges. They can
help maintain a high degree of accuracy and consistency in bridge inspection data. The
key factors that influence the quality of inspection data include unmanned aerial system
inspection platforms, measurement sensors, measurement environments, and
deterioration conditions.
The scope of work includes (1) to understand actionable inspection activities and
procedures in route planning, sensor preparation and measurement, ground truth
selection, and statistical analysis; (2) to outline assessment matrices and best practices
for drone-based images to achieve a practical level of surface mapping accuracy and
crawler-based nondestructive evaluation (NDE) data to detect internal defects; and (3)
to perform case studies using drones/crawlers, NDE tools, photogrammetry software,
and ground control and check points.
The proposed guidelines cover the basic principles of remote sensing and NDE,
contact inspection of fracture critical elements, non-contact inspection based on visual,
thermal, and hyperspectral imaging, calibration procedure and criteria of cameras and
LiDAR scanner, and field demonstration of emerging technologies for crack, corrosion,
delamination, and spalling detection in bridge elements. The QA/QC guidelines are
illustrated in field applications to multi-girder bridges with a highlighted hybrid vehicle
flying to the region of a bridge and engaging with the bridge girder for detailed
inspection on a stationary platform. |