Commenced in January 2007
Paper Count: 30077
Numerical Simulations of Acoustic Imaging in Hydrodynamic Tunnel with Model Adaptation and Boundary Layer Noise Reduction
Abstract:The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1128777Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 552
 T. F. Brooks and W. Humphreys, “A deconvolution approach for the mapping of acoustic sources (DAMAS) determined from phased microphone arrays,” Journal of Sound and Vibration, vol. 294, no. 4–5, pp. 856 – 879, 2006.
 P. Sijtsma, “Clean based on spatial source coherence,” International journal of aeroacoustics, vol. 6, no. 4, pp. 357–374, 2007.
 V. Fleury and R. Davy, “Beamforming-based noise level measurements in hard-wall closed-section wind tunnels,” in Proceedings of the 18th AIAA/CEAS Aeroacoustics Conference, 2012, pp. 1–22.
 L. Koop and K. Ehrenfried, “Microphone-array processing for wind-tunnel measurements with strong background noise. 14th aiaa/ceas aeroacoustics conference, Vancouver, BC, Canada,” AIAA-2008-2907, Tech. Rep., 2008.
 B. Fenech, “Accurate aeroacoustic measurements in closed-section hard-walled wind tunnels,” Ph.D. dissertation, University of Southampton, 2009.
 C. J. Fischer, Jeoffrey R. Doolan, “An empirical de-reverberation technique for closed-section wind tunnel beamforming,” American Institute of Aeronautics and Astronautics 22nd AIAA/CEAS Aeroacoustics Conference, Lyon, France, 2016.
 D. Blacodon, “Spectral estimation method for noisy data using a noise reference,” Applied Acoustics, vol. 72, no. 1, pp. 11 – 21, 2011.
 J. Wright, A. Ganesh, S. Rao, Y. Peng, and Y. Ma, “Robust principal component analysis: Exact recovery of corrupted low-rank matrices via convex optimization,” in Advances in neural information processing systems, 2009, pp. 2080–2088.
 H. Kuttruff, Room acoustics. Crc Press, 2009.
 L. Eld´en, “Algorithms for the regularization of ill-conditioned least squares problems,” BIT Numerical Mathematics, vol. 17, no. 2, pp. 134–145, 1977.
 A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM J. Img. Sci., vol. 2, no. 1, pp. 183–202, Mar. 2009.
 Z. Lingling, W. Huaxiang, X. Yanbin, and W. Da, “A fast iterative shrinkage-thresholding algorithm for electrical resistance tomography,” WSEAS Transactions on Circuits and Systems, vol. 10, no. 11, pp. 393–402, 2011.
 M. Bull, “Wall-pressure fluctuations beneath turbulent boundary laers: some reflections on forty years of research,” Journal of Sound and Vibration, vol. 190, no. 3, pp. 299 – 315, 1996.
 M. Howe, Acoustics of fluid-structure interactions. Cambridge university press, 1998.
 M. Goody, “An Empirical Spectral Model of Surface-Pressure Fluctuations That Includes Reynolds Number Effects,” American Institute of Aeronautics and Astronautics, 2002.
 M. Aucejo, “Vibro-acoustique des structures immerg´ees sous ´ecoulement turbulent,” Ph.D. dissertation, INSA de Lyon, 2010.
 Y. Hwang, W. Bonness, and S. Hambric, “On modeling structural excitations by low speed turbulent boundary layer flows,” DTIC Document, Tech. Rep., 2003.