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Ultrasonic Phased Array Total Focusing Method of Imaging with Rayleigh Waves Based on Principal Component Analysis

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Abstract

Rayleigh waves can be used to detect surface defects effectively. However, the Rayleigh wave imaging quality is often poor due to the low reflected energy when using a single probe. To accomplish high-resolution imaging of surface defects, we propose a total focusing method with Rayleigh waves (TFMRW) combined with principal component analysis (PCA), in an approach called TFMRW-PCA. Firstly, the propagation characteristics of Rayleigh waves are analysed using simulation, and full matrix capture (FMC) data are obtained. Secondly, we use the Fermat principle to calculate the time of flight of the ultrasonic waves, and an improved TFM (TFMRW) algorithm is established to post-process the FMC data. Finally, PCA is used to separate the interference wave from the signal after processing by the TFMRW algorithm. In this paper, the effect of the quantity of elements and the location of the defect on the imaging results are analysed through simulation and experiment. The results show that TFMRW can accurately characterise the surface defects in the sample, with an average defect size error of 0.14 mm2. Moreover, when combined with PCA, the average API value is reduced by 0.06 and the average signal-to-noise ratio (SNR) is increased by 6.26 dB.

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REFERENCES

  1. Shen, X., Hu, H., Li, X., et al., Study on PCA-SAFT imaging using leaky Rayleigh waves, Measurement, 2021, vol. 170, p. 108708.

    Article  Google Scholar 

  2. Katsumata, G., Li, Y., and Hasegawa, K., Remaining lives of fatigue crack growths for pipes with subsurface flaws and subsurface-to-surface flaw proximity rules, J. Pressure Vessel Technol., 2016, vol. 138, no. 5, p. 051402.

  3. Xiang, L., Greenshields, D., and Dixon, S., Phased electromagnetic acoustic transducer array for Rayleigh waves surface defect detection, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 2020, vol. 67, no. 7, pp. 1403–1411.

    Article  Google Scholar 

  4. Jin, S., Yang, X.X., and Chen, S.L., Development and application of ultrasonic phased array detection technology, J. Electron. Meas. Element Instrum., 2014,vol. 28, no. 9, pp. 925–934.

    Google Scholar 

  5. Viktorov, I.A., Rayleigh and Lamb Waves: Physical Theory and Applications, New York: Plenum, 1967.

    Book  Google Scholar 

  6. Jenot, F., Fourez, S., Ouaftouh, M., and Duquennoy, M., Nondestructive testing of thin films using surface acoustic waves and laser ultrasonics, AIP Conf. Proc., 2018, vol. 1949, no. 1, p. 230031.

    Article  Google Scholar 

  7. Wu, J.C., Hu, H.W., Song, Y.F., Duo Lyu, and Li, X.B., Ultrasonic phased array phase shift migration imaging of irregular surface components using attenuation compensation and anti-aliasing technique, NDT&E Int., 2023, vol. 133, p. 102759.

    Article  Google Scholar 

  8. Zhang, S.Z., Li, X.B., and Hyunjo, J., Phased array beam fields of nonlinear Rayleigh surface waves, Chin. Phys. Lett., 2016, vol. 33, no. 7, p. 074302.

    Article  Google Scholar 

  9. Lunci, X., David, G., Steve, D., and Rachel S.E., Phased electromagnetic acoustic transducer array for Rayleigh wave surface defect detection, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 2020, vol. 67, no. 7, pp. 1403–1411.

    Article  Google Scholar 

  10. Yoshikazu, O., Hiromichi, N., et al., Nonlinear surface-acoustic-wave phased array with fixed-voltage fundamental wave amplitude difference for imaging closed cracks, NDT & E Int., 2019, vol. 108, pp. 0963–8695.

    Google Scholar 

  11. Hu, H.W., Du, J., Xu, N., et al., Ultrasonic sparse-TFM imaging for a two-layer medium using genetic algorithm optimization and effective aperture correction, NDT & E Int., 2017, vol. 90, pp. 24–32.

    Article  Google Scholar 

  12. Bazulin, A.E., Bazulin, E.G., and Vopilkin, A.Kh., Testing samples made of polymer composite materials using ultrasonic antenna arrays, Russ. J. Nondestr. Test., 2022, vol. 58, no. 6, pp. 411–424.

    Article  Google Scholar 

  13. Schmerr, L.W., Fundamentals of Ultrasonic Phased Arrays, Berlin: Springer, 2014.

    Google Scholar 

  14. Bazulin, A.E., Bazulin, E.G., Vopilkin, A.Kh., and Tikhonov, D.S., Reconstructing the image of reflectors at base-metal-weld interface using ultrasonic antenna arrays, Russ. J. Nondestr. Test., 2021, vol. 57, no. 9, pp. 739–752.

    Article  Google Scholar 

  15. Zhang, S.Z., Li, X.B., and Hyunjo, J., Measurement of Rayleigh wave beams using angle beam wedge transducers as the transmitter and receiver with consideration of beam spreading, Sensors, 2017, vol. 17, p. 1449.

    Article  Google Scholar 

  16. Oettler, J., Schmid, V.S., Zankl, N., Rey, O., Dress, A., and Heinze, J., Fermat’s principle of least time predicts refraction of ant trails at substrate borders, PLoS ONE, 2013, vol. 8, no. 3, p. e59739.

    Article  CAS  Google Scholar 

  17. Ding, W. and Li, Z., Research on adaptive modulus maxima selection of wavelet modulus maxima denoising, J. Eng., 2019, vol. 2019, no. 13, pp. 175–180.

    Article  Google Scholar 

  18. Gajjar, S., Kulahci, M., and Palazoglu, A., Real-time fault detection and diagnosis using sparse principal component analysis, J. Process Control, 2017, p. S0959152417300677.

  19. Xu, L., Li, J., Shu, Y., et al., SAR image denoising via clustering-based principal component analysis, IEEE Trans. Geosci. & Remote Sens., 2014, vol. 52, no. 11, pp. 6858–6869.

    Article  Google Scholar 

  20. At-Sahalia, Y. and Xiu, D., Principal component analysis of high-frequency data, J. Am. Stat. Assoc., 2019, vol. 114, no. 525, pp. 287–303.

    Article  Google Scholar 

  21. Miranda., A.M., de Seixas, F.L., and José, M., A principal component-based algorithm for denoising in single channel data (PCA for denoising in single channel data), Measurement, 2015, vol. 60, pp. 121–128.

  22. Zhang, S., Li, X., and Jeong, H., Measurement of Rayleigh wave beams using angle beam wedge transducers as the transmitter and receiver with consideration of beam spreading, Sensors, 2017, p. 1449.

  23. Holmes, C., Drinkwater, B.W., and Wilcox, P.D., Post-processing of the full matrix of ultrasonic transmit-receive array data for non-destructive evaluation, NDT&E Int., 2005, vol. 38, no. 8, pp. 701–711.

    Article  CAS  Google Scholar 

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ACKNOWLEDGMENTS

This work was supported by the National Natural Science Foundation of China (grant no. 52075049), the Natural Science Foundation of Hunan Province (grant nos. 2020JJ2028, 2020JJ5577), Hunan Provincial Key Research and Development Program (grant no. 2022GK2058), the Scientific Research Fund of Hunan Provincial Education Department (grant no. 20C0032), and Hunan Province Key Laboratory of Intelligent Manufacturing Technology for High-performance Mechanical Equipment (Changsha University of Science and Technology) (grant no. 2020YB09).

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Correspondence to Hongwei Hu.

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Liu, Z., Zhang, Z., Lyu, D. et al. Ultrasonic Phased Array Total Focusing Method of Imaging with Rayleigh Waves Based on Principal Component Analysis. Russ J Nondestruct Test 59, 346–358 (2023). https://doi.org/10.1134/S1061830922601118

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  • DOI: https://doi.org/10.1134/S1061830922601118

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