功率谱均衡无源声学测绘

Chunqi Li, Harry R. Clegg, T. Carpenter, D. Cowell, S. Freear, J. Mclaughlan
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引用次数: 1

摘要

被动声测图是一种监测和识别声发射性质的技术,具有源定位和剂量计算的功能。PAM在功能上的两个普遍问题是其定位分辨率有限,以及通过实验方法定量剂量分析的数据校准在世界范围内不一致。减小PAM的点扩散函数(PSF)可以最大限度地减小系统扰动,从而在提高输出性能的同时有利于数据校准。基于功率谱均衡的技术,如球化变换和反卷积,已被用于主动超声模式,以恢复真实图像[1]。本文提出了一种基于倒频谱的时间曝光声学(TEA)反卷积方法(CTEA),并以TEA波束形成器(BF)为基础,讨论了最终的图像质量性能和能量一致性。为了简化计算,通过高性能计算机集群,采用并行运行基准和矩阵波束形成技术对所有BF计算进行了改进,并将TEA和CTEA的计算结果转化为具有柔性视场的极坐标,并用自己的模拟和实验数据进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power spectrum equalized passive acoustic mapping
Passive acoustic mapping (PAM) is a technique to monitor and discern the nature of acoustic emissions with functions of source localization and dose calculation. Two general concerns along with functions of PAM refer to its limited resolution for localization and worldwide inconsistent consensus about data calibration for quantitative dose analyzing via experimental way. Alleviating the point spread function (PSF) of PAM could maximally mitigate the system disturbance, and therefore to benefit the data calibration while enhance the output performance. Power spectrum equalized based techniques such as the sphering transformation and deconvolution have been used in active ultrasound modes to restore true images [1]. In this study, a Cepstrum-based Time Exposure Acoustics (TEA) deconvolution method (CTEA) was proposed into PAM, building on TEA beamformer (BF) to discuss the final image quality performance and energy consistency. All the BF calculations were boosted by paralleled-running benchmark and matrix-beamforming techniques through high-performance computer cluster for computation simplicity, and the results from TEA and CTEA were adapted into polar coordinate with flexible field of view then verified with own set simulation and experimental data.
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