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Monitoring the health of bridges uses various sensors and techniques and provides quantitative and reliable data on the condition of bridges. Among measurable quantities, vibration induced by traffic loads has been known as a good indicator of the condition of bridges, serviceability to pedestrians, fatigue analysis, etc. Here we use non-metric, off-the-shelf, Digital Single-Lens Reflex camera (DSLR) as a sensor and apply a photogrammetric approach to measure three bridges live load traffic vibration.
We first tested our approach with shake-table equipment and showed the reliability of the methodology we use through measuring magnitude and frequency of the shake-table, which was then applied to two highway and one local bridges. The results show that vibrational magnitudes are well within the design recommendations of the American Association of State highway Transportation (AASHTO) and that frequencies are in the range of similar bridges that previously published. Furthermore, by providing velocity and acceleration computed from camera derived displacement, we showed that the proposed method is cost-effective and feasible as well as having a good potential for bridge health monitoring.
YUSHIN AHN
Yushin Ahn received the B. Eng. Degree in civil engineering and the M.Sc. degree in surveying and digital photogrammetry from Inha University, Korea in 1998 and 2000, and the MSc and PhD degree in geodetic science from the Ohio State University, Columbus, in 2005 and 2008 respectively. After 3 years of post-doctoral research at Byrd Polar Research Center, Columbus, OH, he taught at Michigan Technological University 2011-2017. He is currently an assistant professor of Civil and Geomatics Engineering, California State University at Fresno, CA. His research interests include digital photogrammetry, feature tracking, and sensor calibration and integration. Dr. Ahn received the Robert E. Altenhofen Memorial Scholarship from the American Society of Photogrammetry and Remote Sensing and he is a certified Photogrammetrist.
SCOTT PETERSON
Dr. Scott Peterson is an Assistant Professor of Geomatics Engineering in the department of Civil and Geomatics Engineering at Fresno State. He received his Masters (2013) and Doctoral (2018) Degrees from Purdue University in Civil Engineering with a focus in Geomatics Engineering. He is a Professional Land Surveyor in the states of California and Utah, and is a Certified Federal Surveyor. He had 10 years of Industry experience in Land Surveying before returning to school and beginning his teaching career. His research interests are Boundary and Legal principles, Land Surveying, and Remote Sensing Applications such as Terrestrial and Mobile LiDAR and Unmanned Aerial vehicles.
MARYAM NAZARI
Dr. Maryam Nazari is an Assistant Professor of Structural Engineering in the Department of Civil and Geomatics Engineering at CSU, Fresno. Her research interest is the application of seismic-resilient precast concrete solutions for design of structures. During her graduate studies, she worked on a research study funded by the National Science Foundation (NSF). She accomplished large-scale shake table experiments on self-centering precast concrete wall systems at the Network for Earthquake Engineering Simulation (NEES) facility of the University of Nevada at Reno (UNR), with the purpose of investigating the impact of different energy dissipating components of these innovative structural systems on their seismic responses. She also participated in several rehabilitation and strengthening projects during her five-year professional experience as a structural design engineer, seismic specialist, and project manager. She has about 10 peer-reviewed conference proceedings and journal papers and has done more than 10 presentations in national and international conferences as well as technical meetings. Her recent research awards include the ASCE SF Section Outstanding Research Project of the Year, ASCE Fresno Best Research Project (in collaborations with Dr. Tehrani), SEI/ASCE Young Professional Scholarship, and the Iowa State University’s Research Excellence award.
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