Inverse identification of mechanical parameters of high-speed train suspensions submitted to random track irregularities

David Lebel 1, 2 Christian Soize 1 Christine Funfschilling 2 Guillaume Perrin 3
1 MSME - Laboratoire de Modélisation et Simulation Multi Echelle
2 SNCF : Innovation & Recherche
3 DAM/DIF - DAM Île-de-France
Abstract : The objective of the work presented here is the inverse identification of parameters describing the mechanical characteristics of high-speed train suspensions for maintenance purposes. This identification is achieved by comparing simulation results to on-track accelerometric measurements. It requires the introduction of an output predictive error as a noise added to simulation outputs to take into account measure and model uncertainties, the introduction of an objective function defined on the parameter domain, and the optimization of this objective function, performed by an EGO (Efficient Global Optimization) algorithm thanks to the construction of a Kriging metamodel of the objective function.
Keywords : Statistical inverse problem experimental identification high-speed train suspensions random track irregularities kriging metamodel.
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David Lebel, Christian Soize, Christine Funfschilling, Guillaume Perrin. Inverse identification of mechanical parameters of high-speed train suspensions submitted to random track irregularities. 12th International Conference on Structural Safety & Reliability, ICOSSAR 2017, Aug 2017, Vienna, Austria. pp.1-9. ⟨hal-01575047⟩

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