\r\nhave seen an increasing demand for quieter ships in order to fulfil

\r\ncurrent regulations and to reduce the effects on marine life. Hence,

\r\nnew methods dedicated to the characterization of propeller noise,

\r\nwhich is the main source of noise in the far-field, are needed. The

\r\nstudy of cavitating propellers in closed-section is interesting for

\r\nanalyzing hydrodynamic performance but could involve significant

\r\ndifficulties for hydroacoustic study, especially due to reverberation

\r\nand boundary layer noise in the tunnel. The aim of this paper

\r\nis to present a numerical methodology for the identification of

\r\nhydroacoustic sources on marine propellers using hydrophone arrays

\r\nin a large hydrodynamic tunnel. The main difficulties are linked to the

\r\nreverberation of the tunnel and the boundary layer noise that strongly

\r\nreduce the signal-to-noise ratio. In this paper it is proposed to estimate

\r\nthe reflection coefficients using an inverse method and some reference

\r\ntransfer functions measured in the tunnel. This approach allows to

\r\nreduce the uncertainties of the propagation model used in the inverse

\r\nproblem. In order to reduce the boundary layer noise, a cleaning

\r\nalgorithm taking advantage of the low rank and sparse structure of the

\r\ncross-spectrum matrices of the acoustic and the boundary layer noise

\r\nis presented. This approach allows to recover the acoustic signal even

\r\nwell under the boundary layer noise. The improvement brought by

\r\nthis method is visible on acoustic maps resulting from beamforming

\r\nand DAMAS algorithms.","references":"[1] T. F. Brooks and W. Humphreys, \u201cA deconvolution approach for\r\nthe mapping of acoustic sources (DAMAS) determined from phased\r\nmicrophone arrays,\u201d Journal of Sound and Vibration, vol. 294, no. 4\u20135,\r\npp. 856 \u2013 879, 2006.\r\n[2] P. Sijtsma, \u201cClean based on spatial source coherence,\u201d International\r\njournal of aeroacoustics, vol. 6, no. 4, pp. 357\u2013374, 2007.\r\n[3] V. Fleury and R. Davy, \u201cBeamforming-based noise level measurements\r\nin hard-wall closed-section wind tunnels,\u201d in Proceedings of the 18th\r\nAIAA\/CEAS Aeroacoustics Conference, 2012, pp. 1\u201322.\r\n[4] L. Koop and K. Ehrenfried, \u201cMicrophone-array processing for\r\nwind-tunnel measurements with strong background noise. 14th aiaa\/ceas\r\naeroacoustics conference, Vancouver, BC, Canada,\u201d AIAA-2008-2907,\r\nTech. Rep., 2008.\r\n[5] B. Fenech, \u201cAccurate aeroacoustic measurements in closed-section\r\nhard-walled wind tunnels,\u201d Ph.D. dissertation, University of\r\nSouthampton, 2009.\r\n[6] C. J. Fischer, Jeoffrey R. Doolan, \u201cAn empirical de-reverberation\r\ntechnique for closed-section wind tunnel beamforming,\u201d American\r\nInstitute of Aeronautics and Astronautics 22nd AIAA\/CEAS\r\nAeroacoustics Conference, Lyon, France, 2016.\r\n[7] D. Blacodon, \u201cSpectral estimation method for noisy data using a noise\r\nreference,\u201d Applied Acoustics, vol. 72, no. 1, pp. 11 \u2013 21, 2011.\r\n[8] J. Wright, A. Ganesh, S. Rao, Y. Peng, and Y. Ma, \u201cRobust principal\r\ncomponent analysis: Exact recovery of corrupted low-rank matrices via\r\nconvex optimization,\u201d in Advances in neural information processing\r\nsystems, 2009, pp. 2080\u20132088.\r\n[9] H. Kuttruff, Room acoustics. Crc Press, 2009.\r\n[10] L. Eld\u00b4en, \u201cAlgorithms for the regularization of ill-conditioned least\r\nsquares problems,\u201d BIT Numerical Mathematics, vol. 17, no. 2, pp.\r\n134\u2013145, 1977.\r\n[11] A. Beck and M. Teboulle, \u201cA fast iterative shrinkage-thresholding\r\nalgorithm for linear inverse problems,\u201d SIAM J. Img. Sci., vol. 2, no. 1,\r\npp. 183\u2013202, Mar. 2009.\r\n[12] Z. Lingling, W. Huaxiang, X. Yanbin, and W. Da, \u201cA fast iterative\r\nshrinkage-thresholding algorithm for electrical resistance tomography,\u201d\r\nWSEAS Transactions on Circuits and Systems, vol. 10, no. 11, pp.\r\n393\u2013402, 2011.\r\n[13] M. Bull, \u201cWall-pressure fluctuations beneath turbulent boundary laers:\r\nsome reflections on forty years of research,\u201d Journal of Sound and\r\nVibration, vol. 190, no. 3, pp. 299 \u2013 315, 1996.\r\n[14] M. Howe, Acoustics of fluid-structure interactions. Cambridge\r\nuniversity press, 1998.\r\n[15] M. Goody, \u201cAn Empirical Spectral Model of Surface-Pressure\r\nFluctuations That Includes Reynolds Number Effects,\u201d American\r\nInstitute of Aeronautics and Astronautics, 2002.\r\n[16] M. Aucejo, \u201cVibro-acoustique des structures immerg\u00b4ees sous \u00b4ecoulement\r\nturbulent,\u201d Ph.D. dissertation, INSA de Lyon, 2010.\r\n[17] Y. Hwang, W. Bonness, and S. Hambric, \u201cOn modeling structural\r\nexcitations by low speed turbulent boundary layer flows,\u201d DTIC\r\nDocument, Tech. Rep., 2003.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 122, 2017"}