Public defence in civil engineering, M.Sc. Yifu Lan

Bridge Monitoring 2.0: Vehicle-Aware Bridge Health Monitoring

Traditional methods necessitate many sensors installed on the bridge, which results in high costs and maintenance requirements; they are no longer the optimal choice for bridge health monitoring. This work delves into the drive-by bridge inspection method that utilizes vehicles equipped with sensors as an alternative approach. The purpose is to develop algorithmic solutions for vehicle-based bridge health monitoring, extracting key bridge modal parameters and precisely identifying bridge damage. It addresses prevalent challenges and provides innovative algorithms that propel the drive-by bridge inspection method closer to real-world application, paving the way for a practical and economical bridge health monitoring system. 

Four innovative algorithms have been proposed and validated through simulation and experiments. They allow the identification of bridge frequencies using ordinary vehicles (e.g., trucks and buses), under uncertainties such as poor road surfaces. An improved machine learning algorithm exhibits outstanding performance in detecting minor damage of bridges. These methods can be widely applied to bridge health monitoring problems towards an intelligent, fast, cost-effective vehicle-mounted bridge health monitoring system.

Opponent: Associate professor Daniel Cantero Lauer, NTNU Norwegian University of Science and Technology, Norway

Custos: Associate professor Weiwei Lin, Aalto University School of Engineering, Department of Civil Engineering

Contact information of the doctoral student: Yifu Lan, yifu.lan@aalto.fi, Tel. +358504314379

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.

Electronic thesis