The influence of finite sample size on surface impedance determination of materials with low sound absorption at low frequencies

Regular paper

Anna Färm

KTH-Royal Institure of Technology

Wednesday 3 june, 2015, 09:20 - 09:40

0.8 Rome (118)

The most common method to reduce noise is to add sound reducing material on the domain boundaries. One way to model the noise reducing effect of the material is to set its surface impedance as the boundary condition of the domain. The surface impedance can be determined experimentally, either from the standardized methods or by free-field methods. The standardized methods suffer from some drawbacks and are limited to normal or random sound incidence. To determine the surface impedance for specific sound incidence, measurement are performed in free field or in-situ. Several methods have been developed for this purpose and these type of measurements are of interest in this paper. The measurements are performed close to the material surface and based on the knowledge of the sound field from a monopole above an impedance surface, the surface impedance of the material can be derived. In earlier papers, the errors in these methods due to the ideal field description has been investigated both for locally and bulk reacting materials. The effect of signal conditioning, sensor types and unwanted reflections have also been studied. One major concern of the methods are the finite size of the sample, and the influence of the edge diffraction has previously been studied for high absorbing materials at normal incidence. This paper focus on errors associated with the free-field measurements in semi- anechoic rooms for normal and oblique incidence at medium and low frequencies for materials with low absorption. This paper provides an extension to previous studies: theoretical background to why the edge diffracted waves have large influence on the results and means to avoid them are presented. This is studied both theoretically and numerically. Results of parameter studies give guidelines of how to avoid errors due to finite samples when designing the measurement setup.

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