Arbitrary Virtual Array Source Aperture (AVASA) Ultrasound Imaging Technique Using Phased Array Excitation

被引:0
作者
Thulsiram Gantala
Mohan Raj Gurunathan
Krishnan Balasubramaniam
机构
[1] Indian Institute of Technology Madras,Department of Mechanical Engineering, Centre for Non
[2] National Institute of Technology Tiruchirappalli,Destructive Evaluation
来源
Journal of Nondestructive Evaluation | 2023年 / 42卷
关键词
Ultrasonic phase array; Arbitrary virtual array source; FMC–TFM; Beamforming; Ultrasound imaging;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, we proposed an advanced ultrasound imaging technique for enhancing the resolution and reducing the imaging processing time by phased array excitement to create beamforming at virtual source positions. In the conventional full matrix capture (FMC) technique, a single element is used for excitation, limiting the transmitted energy and hence reducing the single-to-noise Ratio (SNR) of the received A-scans. The total focusing method (TFM) is implemented on the vast data volume of the received FMC signals to generate virtually focused imaging, requiring high processing time. Therefore, we have introduced two different scanning techniques to increase transmitted energy by exciting the group of the element to form the virtual source below the transducer: (1) virtual array source aperture (VASA) method consists of multiple virtual sources placed below the center of an active aperture with a fixed focal distance. (2) arbitrary virtual array source aperture (AVASA) method consists of multiple virtual sources located randomly below the active aperture. The ultrasound beam is sequentially excited on each virtual source with predefined delay law. While reception, all the transducers are used to form the FMC. The image generation process is similar to the FMC–TFM method. To demonstrate the imaging capabilities of the proposed techniques, we have performed experimentation on two sets of defective specimens with (a) side-drilled holes (SDHs) and (b) cracks. Experimental results quantitatively compared with conventional FMC–TFM, the proposed method improves the SNR by 35% and reduces computation time by 8 times.
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