论文标题
使用自动分化的声学全息图优化
Acoustic Hologram Optimisation Using Automatic Differentiation
论文作者
论文摘要
声学全息图是现代声学的基石。它在两个维度上编码三维声场，其质量决定了声学系统的性能。仅控制声波相的优化方法被认为是控制波的振幅和相位的方法。在本文中，我们提出了具有自动分化的声学全息图优化算法的DIFF-PAT。我们证明，我们的方法比常规方法具有更高的精度。通过随机生成1000组的最多32个控制点的单侧阵列和单轴阵列来评估DIFF-PAT的性能。改进的声学全息图可用于PAT的广泛应用，而无需对控制PATS的现有系统进行任何更改。此外，我们将DIFF-PAT应用于声学间质材料，并在声学全息图的峰值噪声与信号比率上增加了> 8 dB。
Acoustic holograms are the keystone of modern acoustics. It encodes three-dimensional acoustic fields in two dimensions, and its quality determine the performance of acoustic systems. Optimisation methods that control only the phase of an acoustic wave are considered inferior to methods that control both the amplitude and phase of the wave. In this paper, we present Diff-PAT, an acoustic hologram optimisation algorithm with automatic differentiation. We demonstrate that our method achieves superior accuracy than conventional methods. The performance of Diff-PAT was evaluated by randomly generating 1000 sets of up to 32 control points for single-sided arrays and single-axis arrays. The improved acoustic hologram can be used in wide range of applications of PATs without introducing any changes to existing systems that control the PATs. In addition, we applied Diff-PAT to acoustic metamaterial and achieved an >8 dB increase in the peak noise-to-signal ratio of acoustic hologram.
