This content is not included in your SAE MOBILUS subscription, or you are not logged in.
A Comparison of Near-Field Acoustical Holography Methods Applied to Noise Source Identification
ISSN: 0148-7191, e-ISSN: 2688-3627
Published June 05, 2019 by SAE International in United States
Annotation ability available
Near-Field Acoustical Holography (NAH) is an inverse process in which sound pressure measurements made in the near-field of an unknown sound source are used to reconstruct the sound field so that source distributions can be clearly identified. NAH was originally based on performing spatial transforms of arrays of measured pressures and then processing the data in the wavenumber domain, a procedure that entailed the use of very large microphone arrays to avoid spatial truncation effects. Over the last twenty years, a number of different NAH methods have been proposed that can reduce or avoid spatial truncation issues: for example, Statistically Optimized Near-Field Acoustical Holography (SONAH), various Equivalent Source Methods (ESM), etc. Then, more recently, with the motivation of facilitating the measurement process, the principles of Compressive Sensing (CS) have been introduced in several studies to allow sound fields to be reconstructed based on a relatively small number of microphone measurements (thus making holographic measurements more practical and inexpensive), and these studies have shown promising results when used to identify sound source locations. In the present work, the ESM based on an assumed monopole source distribution was the NAH method studied, and the inverse problem that is required to identify the equivalent source strengths was solved by using two different CS algorithms: Wideband Acoustical Holography (WBH) and l1-norm convex optimization (l1- CVX). Several different source types were chosen to test the reconstruction capabilities of the two algorithms: in particular, concentrated point source distributions, and spatially-extended sources such as baffled plate vibration. The strengths and weaknesses of the two CS algorithms have been identified with reference to results obtained by using SONAH.
CitationShi, T. and Bolton, J., "A Comparison of Near-Field Acoustical Holography Methods Applied to Noise Source Identification," SAE Technical Paper 2019-01-1533, 2019, https://doi.org/10.4271/2019-01-1533.
- Maynard, J.D., Williams, E.G., and Lee, Y. , “Nearfield Acoustic Holography: I. Theory of Generalized Holography and the Development of NAH,” Journal of the Acoustical Society of America 78(4):1395-1413, 1985.
- Schuhmacher, A.P. and Hansen, P.C. , “Sound Source Reconstruction Using Inverse BEM,” in INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 2001, 4, 1870-1875, 2001.
- Williams, E.G. , Fourier Acoustics: Sound Radiation and Nearfield Acoustical Holography (Elsevier, 1999).
- Hald, J. , “Basic Theory and Properties of Statistically Optimized Near-Field Acoustical Holography,” Journal of the Acoustical Society of America 125(4):2105-2120, 2009.
- Jeans, R. and Mathews, I.C. , “The Wave Superposition Method as a Robust Technique for Computing Acoustic Fields,” Journal of the Acoustical Society of America 92(2):1156-1166, 1992.
- Liu, Y. and Bolton, J.S. , “The Use of Non-Collocated Higher Order Sources in the Equivalent Source Method,” in INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 2012, 4, Institute of Noise Control Engineering, 2012.
- Hald, J. “Wideband Acoustical Holography,” in Proceedings of INTER-NOISE 2014, Melbourne, Australia, 2014, 308-320.
- Hald, J. , “Fast Wideband Acoustical Holography,” Journal of the Acoustical Society of America 139(4):1508-1517, 2016.
- Shi, T. Liu, Y., and Bolton, J.S. , “The Use of Wideband Acoustical Holography for Noise Source Visualization,” in INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 252, 2, Institute of Noise Control Engineering, 2016.
- Shi, T., Liu, Y., Bolton, J.S., Eberhardt, F. et al. , “Diesel Engine Noise Source Visualization with Wideband Acoustical Holography,” SAE Technical Paper 2017-01-1874, 2017, doi:10.4271/2017-01-1874.
- Shi, T., Liu, Y., and Bolton, J.S. , “Noise Source Identification in an Under-Determined System by Convex Optimization,” Paper 1472, in Proceedings of Inter-Noise 2018, Chicago, August 2018.
- Chardon, G., Daudet, L., Peillot, A., Ollivier, F. et al. , “Near-Field Acoustic Holography Using Sparse Regularization and Compressive Sampling Principles,” Journal of the Acoustical Society of America 132(3):1521-1534, 2012.
- Grant, M., Stephen B., and Ye, Y. , “CVX: Matlab Software for Disciplined Convex Programming,” 2008.
- Rolf, S. and Hald, J. , “Near-Field Acoustical Holography without the Errors and Limitations Caused by the Use of Spatial DFT,” International Journal of Acoustics and Vibration 6(2):83-89, 2001.
- Wang, Z. and Wu, S.F. , “Helmholtz Equation-Least-Squares Method for Reconstructing the Acoustic Pressure Field,” Journal of the Acoustical Society of America 102(4):2020-2032, 1997.
- Thung, C.Y., Bolton, J.S., and Hald, J. , “Source Visualization by Using Statistically Optimized near-Field Acoustical Holography in Cylindrical Coordinates,” Journal of the Acoustical Society of America 118(4):2355-2364, 2005.
- Suzuki, T. , “L1 Generalized Inverse Beam-Forming Algorithm Resolving Coherent/Incoherent, Distributed and Multipole Sources,” Journal of Sound and Vibration 330(24):5835-5851, 2001.
- Hald, J. , “A Comparison of Iterative Sparse Equivalent Source Methods for near-Field Acoustical Holography,” Journal of the Acoustical Society of America 143(6):3758-3769, 2018.