Virtual SEA: Towards an Industrial Process 2007-01-2302
In the high frequency range, the SEA method has been applied to air borne path with success to predict both internal and external sound environment. Nevertheless, structure-borne prediction is still at issue -especially for cars, in the range 200 to 2000 Hz- as results are widely dependant on subsystem partition and validity of various assumptions required by SEA.
Experimental SEA test technique (ESEA), applied to car bodies, has brought to the fore that SEA power balanced equations could robustly describe structure-borne noise. To make ESEA predictive, the database of measured FRF is simply replaced and enlarged by synthesized data generated from a finite element (FE) model and a selected observation grid of nodes. This technique, called Virtual SEA (VSEA), has been presented at SAE/NVC 2003. Since then, many developments have been carried out to improve the general efficiency of the three main steps of VSEA:
The generation of the band-integrated FRF database (between nodes of the observation grid) is now integrated in the virtual SEA solver. As several millions of band averaged FRF can be required for a full car body analysis, a specific fast FRF synthesis is performed using analytical integration and band-optimized solutions by limiting the number of cross-modal terms in the series solution.
Automatic subsystem partition has been widely improved by developing different algorithms that limit the sensitivity of results to initial conditions.
ESEA loss matrix identification process has been reviewed for better resolution of highly non homogeneous system such as car bodies. The normalization of squared FRF matrix by the input mobility matrix allows a direct determination of subsystems modal density. The dynamics of a very large 3D FE model can thus be compressed into a small SEA loss matrix while preserving local transfer information at all nodal observation points.
Examples of applications are shown on car components.