Robotic Monitoring of Bridge Infrastructure
Mobile robotic platform: a field test

Bridges form critical traffic infrastructure components, whose inspection and monitoring is necessary for ensuring their operational and structural safety. Bridge condition assessment ca today assisted by monitoring schemes, where sensing information is used to extract information on the bridge structure While such schemes typically involve stationary sensors that are attached onto the bridge, a more recent monitoring paradigm relies on use of mobile sensors on drive-by vehicles. An essential task in this respect, lies in identifying the dynamic properties of bridge structure, usually through collection of information on its vibrational behavior.
At the Singapore-ETH Centre, the “Dynamic Mobile Sensing Platform” research module has developed a mobile sensing platform for infrastructure inspection via roving sensors. Mobile sensing allows for collection of such information while alleviating the costly, time-consuming and labor-intensive aspects involved in permanently instrumenting the bridge structures themselves. The FRS research team recently developed a mobile sensing platform, which relies on use of a wheeled robot (RoboMaster EP produced by SZ DJI Technology Co., Ltd.) which incorporates an acceleration and a tilt-based sensor. The programmable robot, whose movement can be remotely controlled with a Python program, acts as an automatic and mobile platform equipped with vibration sensors. By analyzing the vibration signals of the on-board mobile sensors, the dynamic properties, such as the modal parameters of the tested bridge, can be identified.

To validate the robotic mobile sensing platform, two full-scale tests were conducted in Singapore; a first test on a footbridge at the Nanyang Technological University, in collaboration with Prof. Prof. Yuguang Fu and Prof. Siu-Kui (Ivan) Au of NTU, and a second test the College Link overpass at the National University of Singapore, in collaboration with Pro. Chan Ghee Koh (NUS).The purpose of the experiments is to identify the main modal frequencies and recover high spatial-resolution mode shapes of the primary modes of these bridges via use of the mobile sensing platform.
Project Team: Xudong Jian (PhD candidate, Tongji), Kiran Bacsa (PhD candidate, ETHZ/SEC), Liu Wei (PhD candidate, NUS/SEC), Prof. Zhilu Lai (HKUST), Prof. Ye Xia (Tongji), Prof. Eleni Chatzi (ETHZ)