Vehicle scanning for bridge health monitoring
Project Description
Bridges are critical components of transportation networks, and maintaining their structural integrity is essential for safety and reliability. Traditional Structural Health Monitoring (SHM) methods typically involve installing sensors directly on the bridge, which can be costly and difficult to scale. In response, vehicle scanning methods have emerged as a promising alternative, utilizing vehicles as mobile sensing platforms to capture vibration data during crossing. This project seeks to conduct a laboratory-scale vehicle scanning experiment to evaluate the effectiveness of these indirect monitoring approaches, with a particular focus on capabilities such as modal identification.
Supervisor
DIMITRAKOPOULOS Ilias
Quota
4
Course type
UROP1000
UROP1100
UROP2100
UROP3100
Applicant's Roles
The students will
(1) apply system identification on the test bridge and test vehicle using traditional approach
(2) apply vehicle scanning techniques
(1) apply system identification on the test bridge and test vehicle using traditional approach
(2) apply vehicle scanning techniques
Applicant's Learning Objectives
Through this project the students will be able to
1. Design and execute a laboratory‑scale vehicle scanning experiment that captures vibration data from a test bridge while the vehicle traverses it.
2. Apply classical system‑identification techniques to the collected data in order to determine modal parameters (frequencies, mode shapes, damping) of both the bridge and the vehicle.
3. Implement and evaluate vehicle‑scanning algorithms, comparing their performance against conventional on‑bridge sensor results to quantify accuracy and limitations.
4. Process raw vibration signals using signal‑processing tools (FFT, subspace methods, time‑frequency analysis) and produce clear, reproducible data sets for further analysis.
5. Interpret modal identification outputs in the context of bridge health monitoring, identifying potential damage signatures or structural deficiencies.
6. Document all procedures, analyses, and findings in a comprehensive technical report that includes methodology, results, validation steps, and recommendations for future field deployments.
1. Design and execute a laboratory‑scale vehicle scanning experiment that captures vibration data from a test bridge while the vehicle traverses it.
2. Apply classical system‑identification techniques to the collected data in order to determine modal parameters (frequencies, mode shapes, damping) of both the bridge and the vehicle.
3. Implement and evaluate vehicle‑scanning algorithms, comparing their performance against conventional on‑bridge sensor results to quantify accuracy and limitations.
4. Process raw vibration signals using signal‑processing tools (FFT, subspace methods, time‑frequency analysis) and produce clear, reproducible data sets for further analysis.
5. Interpret modal identification outputs in the context of bridge health monitoring, identifying potential damage signatures or structural deficiencies.
6. Document all procedures, analyses, and findings in a comprehensive technical report that includes methodology, results, validation steps, and recommendations for future field deployments.
Complexity of the project
Challenging