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Accelerating Algorithm for Total Focusing Method Imaging Based on Optimization of Full Matrix Data

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Abstract

Total focusing method (TFM) for ultrasonic phased array imaging has the advantages of high imaging resolution, full-scale dynamic focusing and low undetected error rate in ultrasonic detection. However, the problem of long imaging time usually limits its practically applications. The imaging speed can be raised sharply by directly upgrading the detection hardware, but this solution is unavoidable to increase the detection cost. This study is interested in how to improve the TFM imaging speed based on the existing hardware. Thus, an accelerating algorithm combining the asymmetrical optimization mechanism for the full matrix data of ultrasonic array with the sparse one was proposed to simplify the imaging process aiming at reducing the imaging time. Furthermore, TFM imaging experiments of the transverse through hole flaw were finally carried out to evaluate the performance of the proposed algorithm. The results show that in sparse optimization algorithms, the imaging speed of 2 elements sparse is faster and the signal-to-noise ratio of image is higher. The asymmetric optimization and 2 elements sparse optimization are combined in proposed algorithm. The imaging speed of proposed algorithm is improved by 34.56%. Similarly, it is 10.50 and 24.94%, respectively faster than using the asymmetric and 2 elements sparse optimization algorithm. Meanwhile, it is also founded that the signal-to-noise ratio (SNR) of TFM imaging after amplitude optimization is greatly increased by 55.99% without losing the information on the defect characterization. The proposed accelerating algorithm provides an important reference for the practical application of TFM in the ultrasonic phased array flaw detection system.

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Funding

This work was supported by the National Natural Science Foundation of China (NSFC 52075270); Key scientific research projects and soft science research projects of military-civilian integration in Inner Mongolia Autonomous Region (JMZD202209); Science and Technology Plan Project of Inner Mongolia (2020GG0160); Supported By Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(NJYT22063); and Natural Science Foundation of Inner Mongolia (2022MS05006).

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Authors and Affiliations

  1. Inner Mongolia Key Laboratory of Intelligent Diagnosis and Control of Mechatronic Systems, Inner Mongolia University of Science and Technology, 014010, Baotou, Inner Mongolia Province, China

    Junhan Li, Shaofeng Wang & Wenjing Liu

  2. Shanghai Aerospace Equipment Manufacturer Co. Ltd., 201101, Shanghai, China

    Xin Mao

  3. Inner Mongolia North Heavy Industries Group Company Limited, 014033, Baotou, Inner Mongolia Province, China

    Hailing Wang

  4. Inner Mongolia Baotou Steel Xichuang Group Co. Ltd., 014033, Baotou, Inner Mongolia Province, China

    Shengrong Zhou

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  1. Junhan Li
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  2. Shaofeng Wang
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  3. Xin Mao
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  4. Wenjing Liu
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  5. Hailing Wang
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Correspondence to Shaofeng Wang.

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Li, J., Wang, S., Mao, X. et al. Accelerating Algorithm for Total Focusing Method Imaging Based on Optimization of Full Matrix Data. Russ J Nondestruct Test 59, 161–170 (2023). https://doi.org/10.1134/S1061830922600642

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  • DOI: https://doi.org/10.1134/S1061830922600642

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