Semi-empirical calibration of remote microphone probes using Bayesian inference

Master thesis (2023)

Authors

O.K.M. Moriaux Aerospace Engineering

Contributors

R. Zamponi Wind Energy - Aerospace Engineering (supervisor 1)
Christophe Schram von Karman Institute for Fluid Dynamics (supervisor 2)
D. Ragni Wind Energy - Aerospace Engineering (supervisor 2)
Faculty
Aerospace Engineering
Copyright: © 2023 Olivier Moriaux
Calibration Bayesian Inference Pressure measurements Microphone Transfer Function Remote microphone probes
More Info
expand_more

Published Date

17-02-2023

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Aerospace Engineering

Abstract

Unsteady surface pressures shed light on the turbulent structures of boundary layer flow, which dictate for a large part the aerodynamic and aeroacoustic performance of aerodynamic bodies submersed in a flow. Remote microphone probes (RMP), e.g., pinhole probes, provide advantages compared to flush-mounted probes because of their reduced sensing area.
However, they feature a distinct transfer function (TF) that needs to be taken into account for accurate pressure measurements. Many empirical calibration techniques for such probes introduce spurious resonance into the calibration, which propagate to the measurements. In this study, a semi-empirical calibration method is proposed with the aim of removing the spurious resonance in a physics-driven manner that is less reliant on the operator. Bayesian inversion is used to fit an analytic model for the TF of the RMP to the empirical calibration data.