Bayesian estimation of dissipation and sound speed in tube measurements using a transfer-function model
arxiv(2024)
摘要
This study discusses acoustic dissipation, which contributes to inaccuracies
in impedance tube measurements. To improve the accuracy of these measurements,
this paper introduces a transfer function model that integrates diverse
dissipation prediction models. Bayesian inference is used to estimate the
important parameters included in these models, describing dissipation
originating from various mechanisms, sound speed, and microphone positions. By
using experimental measurements and considering a hypothetical air layer in
front of a rigid termination as the material under test, Bayesian parameter
estimation allows a substantial enhancement in characterization accuracy by
incorporating the dissipation and sound speed estimates. This approach
effectively minimizes residual absorption coefficients attributed to both
boundary-layer effects and air medium relaxation. Incorporation of dissipation
models leads to a substantial reduction (to 1%) in residual absorption
coefficients. Moreover, the use of accurately estimated parameters further
enhances the accuracy of actual tube measurements of materials using the
two-microphone transfer function method.
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