The separation and identification of distributed noise sources with local coherence by a subspace equivalent-source method

Abstract

Identification of distributed and locally coherent aerodynamic noise sources, such as airfoil noise and blade noise, attracts considerable attention these years. When using beamforming techniques, errors in source positions may be caused by the assumption of incoherent sources. A subspace equivalent-source method is proposed to decompose and identify different components of sources. Sound pressure radiated from each component is represented by coherent structures of the overall sound field, which are calculated by using the Proper Orthogonal Decomposition. The equivalent-source model is modified for the influence of the flow field and the shear layer by using a geometry method. Truncated Singular Value Decomposition is applied to avoid singularities generated by the inverse problem and reduce errors of source identification. The proposed algorithm is verified by numerical simulations and a benchmark experiment of airfoil noise in the wind tunnel. Leading edge noise, trailing edge noise and tip noise are successfully separated and located. The distribution of each source is estimated more accurately than Conventional Beamforming and deconvolution methods. Source decomposition and intrinsic coherence among equivalent sources both account for better performance.