WIDEBAND MICROPHONE ARRAY SYSTEM FOR SOUND LOCALIZATION AND SPECIES IDENTIFICATION IN WIND FARM ENVIRONMENTS

Abstract

Wind energy facilities provide a sustainable power source but pose a significant threat to birds and bats that traverse these areas. To mitigate this risk, an acoustic monitoring system was designed to track and classify volant species. The system consists of an array of wideband microphones that enable time difference of arrival (TDOA) based 3D source localization using the generalized cross-correlation phase transform (GCC-PHAT) algorithm, accurate to within 1 degree in isolated environments. Furthermore, the microphones utilize a convolutional neural network (CNN) for species identification. The collected data maps migration patterns in the areas surrounding wind energy facilities, providing wind energy companies with actionable insights to adjust operations and reduce harm to wildlife.