Uncertainty quantification for monitoring of civil structures from vibration measurements

Michael Döhler 1 Laurent Mevel 1
1 I4S - Statistical Inference for Structural Health Monitoring
IFSTTAR/COSYS - Département Composants et Systèmes, Inria Rennes – Bretagne Atlantique
Abstract : Health Monitoring of civil structures can be performed by detecting changes in the modal parameters of a structure, or more directly in the measured vibration signals. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. In this talk, a strategy for quantifying the uncertainties of modal parameter estimates from a subspace-based system identification approach is presented and the importance of uncertainty quantification in monitoring approaches is shown. Furthermore, a damage detection method is presented, which is based on the direct comparison of the measured vibration signals without estimating modal parameters, while taking the statistical uncertainty in the signals correctly into account. The usefulness of both strategies is illustrated on data from a progressive damage action on a prestressed concrete bridge.
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Communication dans un congrès
European Geosciences Union General Assembly, Apr 2014, Vienna, Austria. 2014
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Michael Döhler, Laurent Mevel. Uncertainty quantification for monitoring of civil structures from vibration measurements. European Geosciences Union General Assembly, Apr 2014, Vienna, Austria. 2014. 〈hal-01011737〉

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