Ultrasound Imaging Algorithm: Half-Matrix Focusing Method Based on Reciprocity

Abstract

The ultrasonic phased array total focusing method (TFM) has the advantages of high imaging signal-to-noise ratio (SNR) and high defect resolution, but the problem of large amount data capturing and processing limits its practical industrial applications. To reduce the imaging calculation demand of the total focusing method, a half-matrix focusing method (HFM) is proposed based on the acoustic reciprocity. The method simplifies the calculation process of full-matrix data capturing (FMC) and total focus imaging. The experimental results show that the signal obtained by the linear array transceiver sensor is highly consistent, and the imaging resolution and signal-to-noise ratio of the half-matrix focusing method are slightly lower than those of full-matrix focusing method and higher than those of the B-scan imaging. However, compared with TFM, data acquisition and computational efficiency using the HFM have been improved significantly.

Ultrasonic Total Focusing Imaging Method of Multilayer Composite Structures Using the Root‐Mean‐Square (RMS) Velocity

“…is paper uses the experimental setup described in [19] to focus imaging on a single-layer medium, and the imaging results are shown in Figure 5. It can be seen that the imaging quality of the simplified matrix is the same as that of the full matrix.…”

“…Since the amount of postprocessing data is part of the full-matrix data, theoretically, the calculation time of this simplified matrix focusing method (SFM) will also be reduced. To superimpose and offset the random noise of positive and negative values, it is necessary to normalize the captured full-matrix data [18,19].…”

“…To quantitatively analyze the performance of different imaging methods, the image signal-to-noise ratio is used to express the relationship between the defect signal and the noise. e signalto-noise ratio for a defect can be expressed [18,19] by…”

“…Nevertheless, the total focus method is time-consuming due to the large amount of processing data [12]. To improve imaging efficiency, different total focus algorithms have been proposed [14][15][16][17][18][19]. Note that both the algorithms based on TFM are only suitable for homogeneous and isotropic materials.…”

Defect data image enhancement method based on all-focus imaging algorithm

“…However, the amount of data captured by the full matrix capture (FMC) is too large, and the data processing time for phased array equipment with a large number of array elements is long, which limits its industrial practical application [10]. So far, some scholars have reduced the cost of computation by improving full matrix data and computer hardware acceleration algorithms [11][12][13]. In the field of full-focus acceleration algorithm, Guo et al [11] proposed a semi-matrix data model to solve the problem that full-focus algorithm needs to collect a large amount of data and process.…”