A model-based fatigue damage estimation framework is proposed for online estimation of fatigue damage, for structural systems by integrating operational vibration measurements in a high-fidelity, large-scale, finite element (FE) model and applying a fatigue damage accumulation methodology. To proceed with fatigue predictions, one has to infer the stress response time histories characteristics based on the monitoring information contained in vibration measurements collected from a limited number of sensors attached to a structure. Predictions, like the existence, the location, the time, and the extent of the damage, are possible if one combines the information in the measurements with information obtained from a high-fidelity FE model of the structure. Such a model may be optimized with respect to the data, using state-of-the-art FE model updating techniques. These methods provide much more comprehensive information about the condition of the monitored system than the analysis of raw data. The diagnosed degradation state, along with its identified uncertainties, can be incorporated into robust reliability tools for updating predictions of the residual useful lifetime of structural components and safety against various failure modes taking into account stochastic models of future loading characteristics. Fatigue is estimated using the Palmgren–Miner damage rule, S-N curves, and rainflow cycle counting of the variable amplitude time histories of the stress components. Incorporating a numerical model of the structure in the response estimation procedure, permits stress estimation at unmeasured spots. The proposed method is applied in a steel frame of a real city bus.
Parallel Computing of Large Scale FE Model based on Explicit Lagrangian FEM