Structural source identification

The control of the vibro-acoustic behavior of structures remains a challenging task in many industrial applications. A possible solution is to control the vibration at source. In this situation, the knowledge of excitation sources is required. However, such information is sometimes difficult or even impossible to measure. In this study, we propose to address the problem of identifying mechanical excitations from vibration measurements. The proposed approach is based on a generalized Tikhonov regularization that allows taking into account prior information on the measurement noise as well as on the main characteristics of the source to identify, like its sparsity or regularity. To solve such a regularization problem efficiently, a Generalized Iteratively Reweighted Least-Squares (GIRLS) algorithm is introduced. Obtained numerical and experimental results show the crucial role of prior information on the quality of the source identification and the performance of the GIRLS algorithm. To better explain the influence of prior information, the Bayesian framework is adopted. It is thus shown that the generalized Tikhonov regularization can be seen as a Bayesian regularization using Generalized Gaussian priors.


(a)

(b)
Numerical validation: Identification of mechanical source acting on a plate at 350 Hz - (a) Reference and (b) Identified souce using the Generalized Tikhonov Regularization

(a)

(b)
Experimental validation: Identification of mechanical source exciting the wall of a box at 350 Hz - (a) Experimental set-up and (b) Identified souce on the excited face of the box using the Generalized Tikhonov Regularization

Reference : M. Aucejo, Structural source identification using a generalized Tikhonov regularization, Journal of Sound and Vibration, submitted, 2012.



Laboratoire de Mécanique des Structures et des Systèmes Couplés - LMSSC