De-noising and regularization in generalized NAH for turbomachinery acoustic noise source reconstruction

Abstract

The identification/localization of propulsion noise in turbo machinery plays an important role in its design and in noise mitigation techniques. Nearfield acoustic holography (NAH) is the process by which all aspects of the sound field can be reconstructed based on sound pressure measurements in the nearfield. Efficient and accurate identification of noise sources, particularly in turbomachinery applications, is difficult due to complex noise generation mechanisms. A boundary element model which describes the transfer function between measurement data (acoustic pressure measurements acquired through microphones placed in close proximity to the test object) and acoustic noise sources within the turbofan duct are used for source reconstruction. This paper investigates the application of data smoothing techniques on source reconstruction in inverse boundary element method NAH. IBEM is chosen as the surfaces of turbomachinery are arbitrarily shaped. The measurement data is smoothed prior to inversion, and two separate smoothing (or denoising) techniques�exploratory data analysis and wavelet denoising�are compared for accuracy. Acoustic noise sources are subsequently estimated from the smoothed data using truncated singular value decomposition (TSVD) based regularized inversion techniques.