Description
This study aims to predict the depth of scour hole developed around a bridge pier with one smart rock. A 3-axis magnetometer was assembled on an unmanned aerial vehicle (UAV) to measure magnetic fields before and after the smart rock has been deployed as the UAV flew around the bridge pier. A 3-axis high resolution GPS unit was fixed on the UAV to ensure accurate measurements of the latitude, longitude and altitude of the magnetometer. The GPS and the magnetometer measurements were synchronized to output the coordinate and magnetic field intensity correspondingly. A simple optimization algorithm was used to predict the position of the smart rock with an accuracy of less than 0.5 m. In addition, a lab test was performed to understand the effect of UAV motors on the intensity of magnetic field. The test results demonstrated that the UAV motors had negligible influence on the magnetic intensity measured at a distance of over 0.75 m. The UAV-based rock positioning method was compared favorably with the traditional crane-based rock positioning method in multiple field tests.
Location
St. Louis, Missouri
Presentation Date
06 Aug 2019, 3:15 pm - 3:35 pm
Meeting Name
INSPIRE-UTC 2019 Annual Meeting
Department(s)
Civil, Architectural and Environmental Engineering
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Source Publication Title
Proceedings of the 9th International Conference on Structural Health Monitoring of Intelligent Infrastructure (2019: Aug. 4-7, St. Louis, MO)
Included in
UAV-Based Smart Rock Positioning for Determination of Bridge Scour Depth
St. Louis, Missouri
This study aims to predict the depth of scour hole developed around a bridge pier with one smart rock. A 3-axis magnetometer was assembled on an unmanned aerial vehicle (UAV) to measure magnetic fields before and after the smart rock has been deployed as the UAV flew around the bridge pier. A 3-axis high resolution GPS unit was fixed on the UAV to ensure accurate measurements of the latitude, longitude and altitude of the magnetometer. The GPS and the magnetometer measurements were synchronized to output the coordinate and magnetic field intensity correspondingly. A simple optimization algorithm was used to predict the position of the smart rock with an accuracy of less than 0.5 m. In addition, a lab test was performed to understand the effect of UAV motors on the intensity of magnetic field. The test results demonstrated that the UAV motors had negligible influence on the magnetic intensity measured at a distance of over 0.75 m. The UAV-based rock positioning method was compared favorably with the traditional crane-based rock positioning method in multiple field tests.
