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The effectiveness of vehicle design' modifications based on an experimental SEA model will strongly depend on the confidence one can have in the identified model. This paper deals with the estimation of the variances of the experimentally derived internal and coupling loss factors, allowing to assess the confidence levels of the SEA predictions. The theory concerning the statistical aspects of the Power Injection Method (PIM) is outlined and the derived analytical expressions are validated based on a Monte-Carlo variability analysis. The statistical formulas are then applied to a railway carriage of a high-speed train, illustrating that the calculation of confidence levels is a very useful tool to assess the accuracy of the experimental SEA model.

Over the last years, SEA has been recognized as a useful tool to model and analyze the high-frequency vibro-acoustic behavior of fully assembled complex structures. This paper discusses the experimental derivation of the loss factor model of a passenger car. The paper outlines the different steps which need to be taken to obtained a fully validated experimental SEA model. This includes the subdivision into subsystems, the PIM measurement campaign, the derivation of the loss factors and their associated confidence levels and the model validation. The paper further details how the experimental SEA model was used to quantify and investigate the airborne and structure-borne contributions to the interior noise level for a road noise test condition. The operational power inputs to the vehicle were indirectly determined from operational response measurements. A contribution analysis showed that airborne noise sources dominated structure-borne noise sources above 500Hz.