Public defence in civil engineering, M.Sc. Zhenkun Li
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Monitoring the health conditions of bridges using vibrations of passing vehicles
This study focuses on structural health monitoring of bridges. The main objective of this work is to extract the bridge’s dynamic information from the passing vehicle’s vibrations and assess the health conditions of the bridge. Methods developed in this thesis are closely related to damage detection, finite element model updating, signal processing, and artificial intelligence. Compared to the traditional ways to install numerous sensors on bridges, this research brings a novel and economical solution for bridge inspection work.
When the vehicle passes a bridge, it can collect the vibrations of the bridge simultaneously, which provides the potential to monitor bridge conditions using vehicular data. To identify the bridge’s frequencies, the contact-point accelerations of a 3D vehicle model are employed instead of accelerations directly collected from the vehicle. It was found that the bridge’s first several frequencies can be identified from the residual contact-point responses of the vehicle. Furthermore, damage to the bridge is successfully detected, localized, and quantified using the identified bridge frequencies from the vehicle when another parked truck is utilized at different bridge locations. In practical engineering, many influence factors can hinder bridge information extraction from vehicle responses. Therefore, this work employs and develops cutting-edge machine learning and deep learning techniques for bridge damage detection using vehicle accelerations. We demonstrate that damage to the bridge can be detected in both supervised and unsupervised manners.
Opponent: Associate professor Maria Giuseppina Limongelli, Politecnico di Milano, Italy
Custos: Associate professor Weiwei Lin, Aalto University School of Engineering, Department of Civil Engineering
Contact information of the doctoral student: Zhenkun Li, zhenkun.li@aalto.fi, puh. +358504737660
The public defence will be organised on campus (auditorium E, Otakaari 1).
The thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.