Super resolution patch near-field acoustic holography via sparse Bayesian learning

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Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (16) : 104-110.

HU Yu1，HU Dingyu1，FANG Yu1，XIAO Yue2

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Abstract

An approach for super resolution patch near-field acoustic holography was proposed based on sparse Bayesian learning.The interpolation and extrapolation models were first established by use of the Gaussian kernel functions and the sparse Bayesian learning, and then the measured pressure was simultaneously interpolated and extrapolated to obtain a larger and denser virtual measurement.Finally, the interpolated and extrapolated pressures were used to perform near-field acoustic holography.Results of the simulation and experiment show that the aperture effect was greatly suppressed and the super resolution reconstruction can be achieved when using the Fourier-based near-field acoustic holography.It also shows that the measurement noise was suppressed in the process of interpolation.

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Patch NAH / sparse Bayesian learning / data interpolation / data extrapolation

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HU Yu1，HU Dingyu1，FANG Yu1，XIAO Yue2. Super resolution patch near-field acoustic holography via sparse Bayesian learning[J]. Journal of Vibration and Shock, 2018, 37(16): 104-110

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