Abstract

This work deals with Experimental Modal Analysis and vibro-acoustic testing performed on several composite panels tested at Leonardo Laboratories, Pomigliano site. The main objective of this paper is to investigate the dynamical behaviour of the structure under test and to evaluate its acoustic properties. Several tests have been performed at the Trasmission Loss Facility of Leonardo.In a modal test, both the applied forces and vibration responses of the excited structure are measured in one or more locations. Exploiting this data, a Modal Model, that essentially contains the same information as the original vibration data, is derived by means of frequency-domain system identification techniques. A home-built Matlab algorithm, named “uMan”, is developed to perform a full Experimental Modal Analysis. Its performances, in terms of capability to build a useful stabilization chart and to curve-fit measured FRFs, are shown. Moreover, a comparison with respect to the state-of-art “Polymax” algorithm in LMS Test.Lab is provided. Finally, the numerical-experimental correlation is performed to verify consistency.The proposed algorithm identifies first mathematical polynomial models, rather than estimating the modal parameters directly from the measurements. Subsequently, these mathematical models are related to the modal parameters. Finally, the obtained Modal Model is compared to the analytical dataset.An acoustic test has been performed to experimentally investigate sound transmission. Two experimental methods have been adopted to evaluate the transmission loss. First, the method that includes measurements of the sound pressure levels using microphones is exploited. Then, the sound intensity method, in which the transmitted sound intensity is measured with a sound intensity probe, is used. By comparing both experimental techniques, the first showed better performance with respect to the other method at low frequencies, while the sound intensity method is more applicable in the medium and high frequency regions in order to predict the noise transmission characteristics.

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