Automatic source localization and spectra generation from deconvolved beamforming maps

We present two methods for the automated detection of aeroacoustic source positions in deconvolved beamforming maps and the extraction of their corresponding spectra. We evaluate these methods on two scaled airframe half-model wind-tunnel measurements. The first relies on the spatial normal distribution of aeroacoustic broadband sources in CLEAN-SC maps. The second uses hierarchical clustering methods. Both methods predict a spatial probability estimation based on which aeroacoustic spectra are generated.