Suitability of dynamic identification for damage detection in the light of uncertainties on a cable stayed footbridge

Structural identification is a very important task especially in all those countries characterized by significant historical and architectural patrimony and strongly vulnerable infrastructures, subjected to inherent degradation with time and to natural hazards e.g. seismic loads. Structural response of existing constructions is usually estimated using suitable numerical models which are driven by a set of geometrical and/or mechanical parameters that are mainly unknown and/or affected by different levels of uncertainties. Some of these information can be obtained by experimental tests but it is practically impossible to have all the required data to have reliable response estimations. For these reasons it is current practice to calibrate some of the significant unknown and/or uncertain geometrical and mechanical parameters using measurements of the actual response (static and/or dynamic) and solving an inverse structural problem. Model calibration is also affected by uncertainties due to the quality (e.g. signal to noise ratio, random properties) of the measured data and to the algorithms used to estimate structural parameters. In this thesis a new robust framework to be used in structural identification is proposed in order to have a reliable numerical model that can be used both for random response estimation and for structural health monitoring. First a parametric numerical model of the existing structural system is developed and updated using probabilistic Bayesian framework. Second, virtual samples of the structural response affected by random loads are evaluated. Third, this virtual samples are used as virtual experimental response in order to analyze the uncertainties on the main modal parameters varying the number and time length of samples, the identification technique and the target response. Finally, the information given by the measurement uncertainties are used to assess the capability of vibration based damage identification method.