A unified Bayesian formulation for the identification of force sources

Abstract

Structures undergo some mechanical impacts during their life phase, which may create high vibration levels that induce damage and failure of the system itself. However, the mechanical characteristics of the shock are often not well known and inverse methods are generally used to estimate these complex sources. Among all the existing methods, Kalman filtering provides a lightweight and elegant solution to solve force reconstruction problems in time domain. In the literature, several Kalman-like filters have been proposed. We demonstrate in this contribution that all these formulations can be unified by expressing them from a Bayesian perspective.

Mathieu Aucejo

Associate Professor

My research interests include inverse problems, vibration control and vibro-acoustics.