De-noising of radiation pressure signal generated by bubble oscillation based on ensemble empirical mode decomposition

Zheng, Xianghao; Zhang, Yuning

doi:10.1007/s42241-022-0065-9

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…The method is widely used for the prediction of different types of cavitation noise. [3] However, it treats the entire cavitation region as a whole to calculate the noise, and thus can only layout the low-frequency noise induced by large-scale cavitation structures, rather than predicting the high-frequency components radiated by small-scale cavitation bubbles. Yamada et al [4] , Bosschers et al [5] developed a cavitation noise prediction approach that melds theoretical and empirical elements, drawing insights from aggregated experimental cavitation noise data.…”

Section: Introductionmentioning

confidence: 99%

Numerical study of the acoustic spectrum of bubble clusters

Deng,

Zhao,

Zhang

et al. 2024

Preprint

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This study delved into the acoustic spectrum of bubble clusters, each consisting of 352 vapor bubbles across volume fractions ranging from 0.005–40%. The clusters, organized in five distinct layers, were modeled using the Volume of Fluid (VOF) method to capture the bubble interfaces, and the Ffowcs Williams-Hawkings (FW-H) methodology to compute the far-field acoustic pressure from bubble collapse. Further analysis revealed distinct sound pressure behaviors across different volume fractions: For 25%-40%, time-domain analysis shows that the peak acoustic pressure pulses from the two innermost layers of bubbles are significantly higher than those from the outer layers. In the frequency domain, the octave decay rate of the acoustic pressure levels is relatively low, around − 3dB/octave. For 0.5%-25%, four acoustic pressure pulses with similar widths and peak values were observed in the time domain. In the frequency domain, there are three distinct peaks in sound pressure levels(SPL), directly linked to the difference in collapse times of bubbles within the cluster, and the octave decay rate accelerates as the volume fraction decreases, stabilizing at -6dB/octave when the volume fraction is reduced to 17.5%. For 0.005%-0.5%, as the volume fraction decreases from 0.5–0.1%, the number of acoustic pressure pulses significantly reduces. Below 0.1% volume fraction, only a single wider pulse is observed. In the frequency domain, the octave decay rate gradually increases with decreasing volume fraction, significantly exceeding − 10dB/octave when it drops below 0.1%, reaching up to -11.7dB/octave.

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Section: Introductionmentioning

confidence: 99%

Numerical study of the acoustic spectrum of bubble clusters

Deng,

Zhao,

Zhang

et al. 2024

Preprint

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Acoustic feature extraction of radiation pressure signal induced by bubble oscillation under dual-frequency acoustic excitation based on CEEMDAN and bubble entropy

Zheng,

Zhang,

2024

International Journal of Fluid Engineering

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Acoustic feature extraction of radiation pressure signals (RPSs) induced by bubble oscillations is a crucial task in the characterization of the properties of underwater objects. In this article, to improve the extraction accuracy, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and bubble entropy (BE) algorithms are combined to extract the effective acoustic components of the RPS. For verification, the proposed extraction scheme is applied to a typical simulated RPS under dual-frequency acoustic excitation. Compared with other extraction methods, CEEMDAN can extract richer acoustic feature information from the RPS, including accurate values for the amplitude and period of oscillation. Furthermore, when the components of the simulated RPS become more complex, the CEEMDAN–BE scheme gives better evaluation results than other schemes in terms of three evaluation indices. Under complex conditions, the signal extraction performances of singular value decomposition and ensemble empirical mode decomposition decrease greatly, but CEEMDAN retains its high signal extraction efficiency, which further confirms the effectiveness of the proposed signal extraction scheme.

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De-noising of radiation pressure signal generated by bubble oscillation based on ensemble empirical mode decomposition

Cited by 2 publications

References 27 publications

Numerical study of the acoustic spectrum of bubble clusters

Numerical study of the acoustic spectrum of bubble clusters

Acoustic feature extraction of radiation pressure signal induced by bubble oscillation under dual-frequency acoustic excitation based on CEEMDAN and bubble entropy

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