Keynote Speaker: Geert Lombaert

Professor Geert Lombaert

Title: Railway bridge KW51 as a testbed for virtual sensing and structural health monitoring
Affiliation: KU LEuven - Bouwmechanica, Leuven (Arenberg) Kasteelpark Arenberg 40 - bus 2448 3001 Leuven

In recent years, the development and use of virtual sensing techniques have seen an increased interest in structural engineering. In virtual sensing, data from a limited number of sensors are combined with complementary information of the system to estimate other quantities of interest. Filtering methods offer a consistent virtual sensing framework as they fuse information that originates from sensors with numerical simulations, taking into account the respective uncertainties. The original Kalman filter enables state estimation for linear time-invariant systems and has been applied to a wide variety of problems in many different fields since its introduction in 1960. 

Recent extensions which have also been applied in structural engineering include the treatment of nonlinear and time-variant systems as well as systems with unknown input and unknown parameters. The developments in filtering methods are particularly appealing in the current setting of structural engineering where, on the one hand, sensing systems provide unprecedented ways to observe structures while, on the other hand, developments in simulation tools enable the construction of detailed computational models that closely mimic the behavior of real structures. Inspired by successful laboratory tests of combined state, input, and parameter estimation, a monitoring system was recently installed on railway bridge KW51 to validate the use of virtual sensing methods for fatigue assessment, by extrapolating a sparse set of strains measured to other locations. In this talk, we will address the challenges and difficulties in the application of the virtual sensing method. 

In addition, we will also elaborate on a number of side projects which were triggered by the monitoring project and present the bridge as a testbed for structural health monitoring (SHM) methods, including opportunities for population-based SHM, as well as the consideration of the bridge behavior under combined thermal and structural loads.

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