Farfield and Nearfield Source Identification for Machine Tools Using Microphone Array Imaging Systems

Abstract Farfield and nearfield microphone arrays are proposed for noise source identification (NSI) and sound field visualization (SFV). Farfield acoustic imaging algorithms including the delay and sum (DAS) algorithm, the minimum variance distortionless response (MVDR) algorithm and the multiple signal classification (MUSIC) algorithm are employed to estimate direction of arrival (DOA). Results demonstrate that the MUSIC algorithm can attain the highest resolution of localizing sound sources positions. In the nearfield array signal processing, one formulation termed the indirect equivalent source model (ESM)-based nearfield acoustical holography (NAH) is derived from discretizing the simple layer potential. As indicated by the experimental results, the proposed technique proved effective in identifying the noise sources from various machine tools such as milling machine, turning lathe and shearing machine.

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