Section: New Results

Large structures identification - Data fusion

Participants : Michael Döhler, Laurent Mevel.

See modules  3.2 , 3.5 , 4.2 , and  7.7 .

In Operational Modal Analysis (OMA) of large structures we often need to process sensor data from multiple non simultaneously recorded measurement setups. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. To obtain the modal parameters of the investigated structure, it is necessary to process the data of all the measurement setups and normalize it as the unmeasured background excitation of each setup might be different. For this we compare three different approaches which differ in the order of the data merging, normalization and system identification step: The classical PoSER (identification-normalization-merging), the PoGER (merging-identification-normalization) and the PreGER (normalization-merging-identification). Special care was taken with the PreGER method and its efficiency has been tested with respect to the two other methods. The system identification is done with the SSI-cov/ref method. We apply these methods to the extraction of the modal parameters (natural frequencies, damping ratios and mode shapes) of the Luiz I arch bridge in Porto, Portugal, compare them and evaluate the different methods [17] .

A variant of this approach has been derived to handle different subspace approaches such as the UPC data driven approach. It has been tested on a building in Vancouver and presented in [16] . This is part of M. Döhler thesis and related to SVIBS agreement.