Expert decision support system to improve the analysis of airframe noise measurements

Abstract

For the localization and estimation of aeroacoustic sources on complex aircraft models in wind tunnel measurements beamforming and related methods are well known. The task of the aeroacoustic experts is to identify and classify the relevant sources within these beamforming maps. In this paper, we present an expert decision support system to support this task. The system comprises three steps: The first step identifies aeroacoustic sources in sparse beamforming maps and extracts their corresponding spectra without manual definition of regions of interest. The second step calculates the acoustic properties of the sources based on spectral and spatial information. The third step clusters the identified sources based on these acoustic properties. In this paper, data are evaluated based on CLEAN-SC beamforming maps of two airframe half-model wind tunnel measurements. A variety of aeroacoustic features are proposed that capture the characteristics of the source spectra. The result of this expert decision support system is a list of all relevant sources clustered according to their acoustic behavior at different Mach numbers. The aim of the system is to support aeroacoustic specialists in analyzing beamforming results and identifying relevant and spurious sources in-situ.