Abstract
The ultrasonic phased array total focusing method (TFM) has the advantages of full-range dynamic focusing and high imaging resolution, but the problem of long imaging time limits its practically industrial applications. To reduce the imaging calculation demand of TFM, the locations of active array elements in the sparse array are optimized by combining almost different sets with the genetic algorithm (ADSGA), and corrected based on the consistency of the effective aperture with the equivalent point diffusion function. At the same time, to further increase the imaging efficiency, a sparse-TFM image with lower resolution is obtained by reducing the number of focus points and then interpolated by the new edge-directed interpolation algorithm (NEDI) to obtain a high quality sparse-TFM image. Compared with TFM, the experimental results show that the quantitative accuracy of the proposed method is only decreased by 1.09% when the number of sparse transmitting elements reaches 8 for a 32-element transducer, and the imaging speed is improved by about 16 times with the same final pixel resolution.
Highlights
Ultrasonic phased array testing has the advantages of high sensitivity and favorable adaptability to complex components, and has been widely used in nondestructive testing for key equipment [1,2,3].Holmes et al [4] firstly proposed the concepts of full matrix capture (FMC) and the full matrix data model, and established the total focusing method (TFM) algorithm using FMC
A corrected sparse-TFM imaging method based on sparse array optimization and new edge-directed interpolation algorithm (NEDI)
Compared with the uniform sparse array and sparse array optimized using GA, the sparse array optimized by almost different sets with the genetic algorithm (ADSGA) has a narrower main-lobe width (MLW) and a smaller peak of side-lobe (PSL)
Summary
Ultrasonic phased array testing has the advantages of high sensitivity and favorable adaptability to complex components, and has been widely used in nondestructive testing for key equipment [1,2,3].Holmes et al [4] firstly proposed the concepts of full matrix capture (FMC) and the full matrix data model, and established the total focusing method (TFM) algorithm using FMC. Compared with conventional ultrasonic phased array testing, TFM can realize the focus of any points within the measured area by post-processing the full matrix data of the transducer array [5,6,7] This method has been increasingly used in the fields of aviation, nuclear power, composite materials and so on [8,9,10]. Due to the large amount of full matrix data involved, TFM imaging calculations are time-consuming, which limits its applications in some industrial fields, especially those with real-time requirements To solve this problem, the computing time can be reduced by improving the hardware architecture using a GPU [11] or parallel computing with multiple Field-Programmable Gate Arrays (multi-FPGA) [12], but the cost will increase significantly.
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