Numerical Simulations of Acoustic Imaging in Hydrodynamic Tunnel with Model Adaptation and Boundary Layer Noise Reduction

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.




References:
[1] 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.
[2] P. Sijtsma, “Clean based on spatial source coherence,” International
journal of aeroacoustics, vol. 6, no. 4, pp. 357–374, 2007.
[3] 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.
[4] 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.
[5] B. Fenech, “Accurate aeroacoustic measurements in closed-section
hard-walled wind tunnels,” Ph.D. dissertation, University of
Southampton, 2009.
[6] 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.
[7] D. Blacodon, “Spectral estimation method for noisy data using a noise
reference,” Applied Acoustics, vol. 72, no. 1, pp. 11 – 21, 2011.
[8] 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.
[9] H. Kuttruff, Room acoustics. Crc Press, 2009.
[10] L. Eld´en, “Algorithms for the regularization of ill-conditioned least
squares problems,” BIT Numerical Mathematics, vol. 17, no. 2, pp.
134–145, 1977.
[11] 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.
[12] 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.
[13] 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.
[14] M. Howe, Acoustics of fluid-structure interactions. Cambridge
university press, 1998.
[15] M. Goody, “An Empirical Spectral Model of Surface-Pressure
Fluctuations That Includes Reynolds Number Effects,” American
Institute of Aeronautics and Astronautics, 2002.
[16] M. Aucejo, “Vibro-acoustique des structures immerg´ees sous ´ecoulement
turbulent,” Ph.D. dissertation, INSA de Lyon, 2010.
[17] Y. Hwang, W. Bonness, and S. Hambric, “On modeling structural
excitations by low speed turbulent boundary layer flows,” DTIC
Document, Tech. Rep., 2003.