No abstract

This study presents a novel strategy for identifying an impact event on a structure from vibration measurements. Compared to triangulation techniques that require at least three sensors on a plate-like structure, only one sensor is used in this work for localizing the impact point. The proposed approach consists in extracting specific modal ponderations as a signature of impact location. The force reconstruction problem is simultaneously addressed by fitting a parametric law. The proposed procedure captures the main load history parameters such as the impact time, its duration and its intensity. An impact test campaign is performed on a metallic plate, equipped with one accelerometer only, to confirm the validity of the proposed single-sensor approach. The methodology is efficient for accurately localizing impacts that are applied anywhere on the plate and for quickly estimating the main load history parameters.

SummaryThe proper orthogonal decomposition (POD) is successfully employed in a variety of projection‐based methods for parametric model order reduction (pMOR) of large dynamical systems. It extracts the most energetic modes describing the dynamics of a system from time snapshots of the solution. In practice, these snapshots are computed at user‐defined parameters of the system with a high fidelity model. Then either all the snapshots are concatenated to extract a global POD basis, or a different POD basis is extracted for each parameter value. In the latter case, for unseen target parameters, the POD bases need to be adapted with a dedicated technique. An established method addressing this task is the interpolation on the tangent space to the Grassmann manifold (ITSGM). It interpolates the linear subspaces spanned by the known POD bases, discarding by construction the knowledge on the modes ordering by energy levels. In this paper, we formalize an ordered reduced basis interpolation (ORBI) technique which preserves such ordering. This approach improves the adaptation accuracy of the resulting POD basis as more information is taken into account in the construction of the interpolation operator. Numerical investigations are conducted on the parametric reduced order model of a dynamical system representing a small‐scale gas‐bearings supported rotor. Results show that the proposed method is more accurate than the ITSGM method at a similar computation cost. Trained at only three points of the parameters space, the developed hyper reduced order model (h‐ROM) performs to faster simulations with satisfactory accuracy, even far from the training points.