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The Øresund Bridge opened in July 2000. It is the most striking part of the fixed link across the Øresund connecting Copenhagen (Denmark) and Malmø (Sweden), which further includes a tunnel and an artificial island. The bridge is equipped with a PC-based continuous monitoring system, capable of measuring both static and dynamic quantities such as temperatures, wind characteristics, air humidity, strains and accelerations. The challenges for the design of the monitoring system were the long distances between the monitoring points and the variety of sensors. This paper describes the bridge and the monitoring system components. Some typical measurement data are presented. Finally, the modal parameters of the bridge are extracted from the deck, cable and tower vibrations. This shows that the system does not only give information about sudden events that exceed a certain threshold, but can also be used as a health monitoring system by tracking the evolution of the modal parameters. [ABSTRACT FROM AUTHOR]

In several cases, laboratory-based modelling approaches such as Experimental Modal Analysis and Transfer Path Analysis run into limitations with respect to technical and economical feasibility (accessibility of the structure, excitation feasibility, measurement time, accuracy, ..) as well as model representativity. Therefore, approaches such as in-operation modal analysis (OMA) have been developed and are reaching a similar degree of acceptability as standard EMA, with all limitations regarding accuracy and observability of the structural dynamics. In the same line of reasoning fits the question of system characterization and identification using (or based on) other operation data types such as transmissibility functions and coherence functions and data analysis procedures such as principal component analysis. Using these testing and analysis paradigms instead of the classical load-FRF-response one, key analysis techniques such as transfer path and contribution analysis can be reconsidered. [ABSTRACT FROM AUTHOR]

In this paper, we discuss optimised strategies to measure the frequency response function in the presence of (non-linear) distortions. To do so we will compare three classes of excitation signals. These signals will be used in an optimised measurement strategy, reducing the leakage effects to acceptable (user-defined) levels, allowing to separate the disturbing noise influence from the impact of non-linear contributions, and resulting in the ‘best linear approximation’ of the system. [Copyright &y& Elsevier]