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Extended-resolution acoustic imaging of low-frequency wave sources by acoustic analogy-based tomography

Published online by Cambridge University Press:  20 July 2020

Wangqiao Chen
Affiliation:
State Key Laboratory of Turbulence and Complex Systems, Aeronautics and Astronautics, College of Engineering, Peking University, Beijing, PR China
Siyang Zhong
Affiliation:
Department of Mechanical and Aerospace Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, PR China HKUST Institute for Advanced Study, Hong Kong University of Science and Technology, Hong Kong SAR, PR China
Xun Huang*
Affiliation:
State Key Laboratory of Turbulence and Complex Systems, Aeronautics and Astronautics, College of Engineering, Peking University, Beijing, PR China
*
Email address for correspondence: huangxun@pku.edu.cn

Abstract

The weakest possible waves in nature are detectable by improving sensitive measurements, but the attainable imaging resolution of low-frequency waves is still challenging, especially in aeroacoustic experiments. In this work, we show how extended-resolution imaging of low-frequency wave sources can be achieved by incorporating acoustic analogy into tomography. First, an equivalent source of sound, which is dependent on the low-frequency target sound field, is produced due to the nonlinear coupling and interaction with an external high-frequency incident plane wave. Next, the low-frequency sources are reconstructed based on the induced sound waves recorded at the receivers. The induced sound waves are of high frequency to enable the extended-resolution imaging. The physical processes involved are theoretically explained based on the insightful acoustic analogy theory and the Born approximation. The numerical and experimental demonstration cases, with representative but straightforward configurations, show that the proposed method can identify the isolated target sources (at low frequencies) with a separation distance smaller than one-tenth to one-thirtieth of the wavelength, yielding much better resolution than the conventional acoustic imaging approaches. The results suggest that the proposed method will be a promising candidate to investigate the properties of an acoustic source within small regions, and, therefore, likely to be used in the study of the associated fluid physics.

Type
JFM Papers
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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References

REFERENCES

Ashcroft, G. & Zhang, X. 2003 Optimized prefactored compact schemes. J. Comput. Phys. 190 (2), 459477.CrossRefGoogle Scholar
Beyer, R. T. 1973 Nonlinear acoustics. Am. J. Phys. 41 (9), 10601067.CrossRefGoogle Scholar
Brooks, T. F. & Humphreys, W. M. 2006 A deconvolution approach for the mapping of acoustic sources (DAMAS) determined from phased microphone arrays. J. Sound Vib. 294 (4–5), 856879.CrossRefGoogle Scholar
Carpio, A. R., Avallone, F., Ragni, D., Snellen, M. & van der Zwaag, S. 2019 Mechanisms of broadband noise generation on metal foam edges. Phys. Fluid 31, 105110.CrossRefGoogle Scholar
Cattafesta, L. N. & Sheplak, M. 2011 Actuators for active flow control. Annu. Rev. Fluid Mech. 43, 247272.CrossRefGoogle Scholar
Chen, J., Xiao, J., Lisevych, D., Shakouri, A. & Fan, Z. 2018 Deep-subwavelength control of acoustic waves in an ultra-compact metasurface lens. Nat. Commun. 9 (1), 4920.CrossRefGoogle Scholar
Christensen, J., Martin-Moreno, L. & Garcia-Vidal, F. J. 2008 Theory of resonant acoustic transmission through subwavelength apertures. Phys. Rev. Lett. 101 (1), 014301.CrossRefGoogle ScholarPubMed
Clarke, J. A., Chatterjee, S., Li, Z. H., Riede, T., Agnolin, F., Goller, F., Isasi, M. P., Martinioni, D. R., Mussel, F. J. & Novas, F. E. 2016 Fossil evidence of the avian vocal organ from the mesozoic. Nature 538 (7626), 502.CrossRefGoogle ScholarPubMed
Dowling, D. R. & Sabra, K. G. 2015 Acoustic remote sensing. Annu. Rev. Fluid Mech. 47, 221243.CrossRefGoogle Scholar
Gloerfelt, X. & Berland, J. 2013 Turbulent boundary-layer noise: direct radiation at mach number 0.5. J. Fluid Mech. 723, 318351.CrossRefGoogle Scholar
He, Y., Zhong, S. Y. & Huang, X. 2019 Extensions to the acoustic scattering analysis for cloaks in non-uniform mean flows. J. Acoust. Soc. Am. 164 (41), 4149.CrossRefGoogle Scholar
Hu, F. Q., Hussaini, M. Y. & Manthey, J. L. 1996 Low-dissipation and low-dispersion Runge–Kutta schemes for computational acoustics. J. Comput. Phys. 124 (1), 177191.CrossRefGoogle Scholar
Huang, X., Zhong, S. Y. & Liu, X. 2014 Acoustic invisibility in turbulent fluids by optimised cloaking. J. Fluid Mech. 749, 460477.CrossRefGoogle Scholar
Jones, N. 2019 Ocean uproar: saving marine life from a barrage of noise. Nature 568, 158161.CrossRefGoogle ScholarPubMed
Kak, A. C., Slaney, M. & Wang, G. 2002 Principles of computerized tomographic imaging. Med. Phys. 29 (1), 107107.CrossRefGoogle Scholar
Kjaer, K., Als-Nielsen, J., Helm, C. A., Laxhuber, L. A. & Möhwald, H. 1987 Ordering in lipid monolayers studied by synchrotron x-ray diffraction and fluorescence microscopy. Phys. Rev. Lett. 58 (21), 2224.CrossRefGoogle ScholarPubMed
Lighthill, M. J. 1952 On sound generated aerodynamically I. General theory. Proc. R. Soc. A 211 (1107), 564587.Google Scholar
Liu, Y. Y., Slotine, J. & Barabási, A. 2013 Observability of complex systems. Proc. Natl. Acad. Sci. USA 110 (7), 24602465.CrossRefGoogle ScholarPubMed
McEvoy, M. A. & Correll, N. 2015 Materials that couple sensing, actuation, computation, and communication. Science 347 (6228), 1261689.CrossRefGoogle Scholar
Melde, K., Mark, A. G., Qiu, T. & Fischer, P. 2016 Holograms for acoustics. Nature 537 (7621), 518522.CrossRefGoogle ScholarPubMed
Merino-Martínez, R., Sijtsma, P., Snellen, M., Ahlefeldt, T., Antoni, J., Bahr, C. J., Blacodon, D., Ernst, D., Finez, A., Funke, S. et al. 2019 A review of acoustic imaging methods using phased microphone arrays. CEAS Aero. J. 10 (1), 197230.CrossRefGoogle Scholar
Miao, J. W., Ishikawa, T., Robinson, I. K. & Murnane, M. M. 2015 Beyond crystallography: Diffractive imaging using coherent x-ray light sources. Science 348 (6234), 530535.CrossRefGoogle ScholarPubMed
Miñano, J. C., Sánchez-Dehesa, J., González, J. C., Benítez, P., Grabovičkić, D., Carbonell, J., & Ahmadpanahi, H. 2014 Experimental evidence of super-resolution better than $\lambda$/105 with positive refraction. New J. Phys. 16 (3), 033015.CrossRefGoogle Scholar
Murray IV, H. H., Devenport, W. J., Alexander, W. N., Glegg, S. A. L. & Wisda, D. 2018 Aeroacoustics of a rotor ingesting a planar boundary layer at high thrust. J. Fluid Mech. 850, 212245.CrossRefGoogle Scholar
Natterer, F. 2001 The Mathematics of Computerized Tomography. SIAM.CrossRefGoogle Scholar
Pendry, J. B., Schurig, D. & Smith, D. R. 2006 Controlling electromagnetic fields. Science 312 (5781), 17801782.CrossRefGoogle ScholarPubMed
Pfeiffer, F., Kottler, C., Bunk, O. & David, C. 2007 Hard x-ray phase tomography with low-brilliance sources. Phys. Rev. Lett. 98 (10), 108105.CrossRefGoogle ScholarPubMed
Richards, S. K., Zhang, X., Chen, X. X. & Nelson, P. A. 2004 The evaluation of non-reflecting boundary conditions for duct acoustic computation. J. Sound Vib. 270 (3), 539557.CrossRefGoogle Scholar
Rodenburg, J. M., Hurst, A. C., Cullis, A. G., Dobson, B. R., Pfeiffer, F., Bunk, O., David, C., Jefimovs, K. & Johnson, I. 2007 Hard-x-ray lensless imaging of extended objects. Phys. Rev. Lett. 98 (3), 034801.CrossRefGoogle ScholarPubMed
Sánchez, E. J., Novotny, L. & Xie, X. S. 1999 Near-field fluorescence microscopy based on two-photon excitation with metal tips. Phys. Rev. Lett. 82 (20), 4014.CrossRefGoogle Scholar
Spanne, P., Thovert, J. F., Jacquin, C. J., Lindquist, W. B., Jones, K. W. & Adler, P. M. 1994 Synchrotron computed microtomography of porous media: topology and transports. Phys. Rev. Lett. 73 (14), 2001.CrossRefGoogle ScholarPubMed
Van Veen, B. D. & Buckley, K. M. 1988 Beamforming: a versatile approach to spatial filtering. IEEE ASSP Mag. 5 (2), 424.CrossRefGoogle Scholar
Viessmann, O. M., Eckersley, R. J., Christensen-Jeffries, K., Tang, M. X. & Dunsby, C. 2013 Acoustic super-resolution with ultrasound and microbubbles. Phys. Med. Biol. 58 (18), 6447.CrossRefGoogle ScholarPubMed
Westervelt, P. J. 1963 Parametric acoustic array. J. Acoust. Soc. Am. 35 (4), 535537.CrossRefGoogle Scholar
Williams, E. G. & Maynard, J. D. 1980 Holographic imaging without the wavelength resolution limit. Phys. Rev. Lett. 45 (7), 554.CrossRefGoogle Scholar
Wu, R. S. & Toksöz, M. N. 1987 Diffraction tomography and multisource holography applied to seismic imaging. Geophysics 52 (1), 1125.CrossRefGoogle Scholar
Xu, H. F., He, Y. O., Strobel, K. L., Gilmore, C. K., Kelley, S. P., Hennick, C. C., Sebastian, T., Woolston, M. R., Perreault, D. J. & Barrett, S. R. H. 2018 Flight of an aeroplane with solid-state propulsion. Nature 563 (7732), 532.CrossRefGoogle ScholarPubMed
Zhang, S., Yin, L. L. & Fang, N. 2009 Focusing ultrasound with an acoustic metamaterial network. Phys. Rev. Lett. 102 (19), 194301.CrossRefGoogle ScholarPubMed