Fast total focusing method for ultrasonic imaging

Abstract

Abstract. Synthetic aperture focusing technique (SAFT) and total focusing method (TFM) have become popular tools in the field of ultrasonic non destructive testing. In particular, they are employed for detection and characterization of flaws. From data acquired with a transducer array, those techniques aim at reconstructing an image of the inspected object from coherent summations. In this paper, we make a comparison between the standard technique and a migration approach. Using experimental data, we show that the developed approach is faster and offers a better signal to noise ratio than the standard total focusing method. Moreover, the migration is particularly effective for near-surface imaging where standard methods used to fail. On the other hand, the migration approach is only adapted to layered objects whereas the standard technique can fit complex geometries. The methods are tested on homogeneous pieces containing artificial flaws such as side drilled holes.

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.…”

“…Bazulin and Medvedev [12] considered the rule problem of full matrix acquisition, further optimized the matrix proposed from sparse pairs of elements and elements, and finally improved data acquisition speed by nearly 4 times while image quality decreased slightly in numerical simulation. Carcreff et al [13] proposed an all-focus imaging algorithm based on frequency domain migration, which accelerated the imaging speed and effectively improved the resolution of the image. Meanwhile, in the field of computer hardware acceleration, Lambert et al [14] accelerated full-focus imaging calculation simply and effectively by using the parallel computing method of computer graphics processing unit (GPU) and general purpose processor (GPP) hardware.…”