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基于声辐射模态和稀疏采样的声场质点振速重建方法

Reconstruction of particle velocity of the sound field based on acoustic radiation modes and sparse sampling

  • 摘要: 压缩感知理论被应用于近场声全息技术用来实现在测量点数有限的情况下提高声场的重建精度。然而目前大多数的应用都集中于声压的重建,相应稀疏基的构建也是针对声压信号。为了实现声场质点振速的高精度重建,本文基于等效源源强的声辐射模态构建了声场质点振速的稀疏基,并通过稀疏正则化实现从有限的测量数据中精确重建声场的质点振速。为验证本文所提方法的有效性,给出了简支板的数值仿真,仿真结果表明,在测量点数较少的情况下,相较于常规等效源法,使用本文提出方法的质点振速重建精度更高,性能更加稳定,实验结果进一步验证了本文所提方法的有效性。

     

    Abstract: Compressive sensing has been applied to near-field acoustic holography technology to improve the reconstruction accuracy of the sound field with limited measurement points. However, most applications focus on the reconstruction of sound pressure, and the corresponding sparse bases is designed for sound pressure. In order to reconstruct the particle velocity of sound field, this paper constructs a sparse basis for particle velocity of sound field based on the sound radiation mode of equivalent source strength, and precisely reconstructs the particle velocity of the sound field from limited measurements by taking advantage of sparse regularization. To verify the effectiveness of the proposed method, numerical simulation of a simply supported plate is provided. The simulation results showed that, compared to that of conventional equivalent source method, the reconstruction result obtained by the proposed method is more accurate and more stable with limited measurement points. And, the experimental results further validate the effectiveness of the method proposed in this paper.

     

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