首页|基2-FFT输入分级截断算法在频域合成孔径超声成像中的研究

基2-FFT输入分级截断算法在频域合成孔径超声成像中的研究

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为提高超声频域成像算法的计算速度,提出一种应用于超声频域成像算法的基2-FFT输入分级截断算法.首先,借助于COMSOL多物理场仿真软件,建立钢件中含有孔缝缺陷的有限元模型进行声场仿真.仿真结果得到关于缺陷的回波信号,并通过PSM算法对频域内声场进行重建,得到成像区域的聚焦图像,和原始仿真信号的B扫图像相比效果更加直观且成像质量更好,验证了PSM算法的可行性.然后为了避免超声频域成像算法中二维傅里叶变换的冗余计算,进一步提出了支持任意非0值输入的基2-FFT输入分级截断算法.实验结果证明,基2-FFT输入分级截断算法比标准基2-FFT算法快27%,超声频域算法成像速度提高13%.
Study of Radix 2-FFT Input Hierarchical Truncation Algorithm in Frequency Domain Synthetic Aperture Ultrasound Imaging
To improve the computational speed of the ultrasonic frequency domain imaging algorithm,a radix-2-FFT input hierarchical truncation algorithm applied to the ultrasonic frequency domain imaging algorithm is proposed.First of all,with the help of COMSOL Multiphysics simulation software,a finite element model containing hole and seam defects in steel parts is established for sound field simulation.The echo signal about the defect is obtained from the simulation results,and the acoustic field in the frequency domain is re-constructed by using the PSM algorithm to obtain the focused image of the imaging area.Compared with the B-scan image of the original simulation signal,the effect is more intuitive and the imaging quality is better,which verifies the feasibility of the PSM algorithm.Then,to avoid redundant computation of 2D Fourier transform in ultrasonic frequency domain imaging algorithm,a radix-2-FFT input hierar-chical truncation algorithm that supports any non-zero value input is further proposed.The experimental results show that the radix-2-FFT input hierarchical truncation algorithm is 27% faster than the standard radix-2-FFT algorithm,and the imaging speed of the algo-rithm in the ultrasonic domain is 13% faster.

ultrasound frequency domain imagingradix-2-FFTB-scan imaginghierarchical truncation algorithmimaging speed

周英钢、刘振兴、王善辉、李继冯

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沈阳工业大学信息科学与工程学院,辽宁 沈阳110870

辽宁科技学院中美双百学院,辽宁 本溪117004

超声频域成像 基2-FFT B扫成像 分级截断算法 成像速度

国家自然科学基金国家自然科学基金

6137215460772064

2024

传感技术学报
东南大学 中国微米纳米技术学会

传感技术学报

CSTPCD北大核心
影响因子:1.276
ISSN:1004-1699
年,卷(期):2024.37(7)