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Ultrasonic Phased Array Imaging for Defects in Angle Blind Spots Based on the Solid Directivity Function

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Abstract

The FMC-TFM is currently a popular method for ultrasonic phased array imaging. In the FMC-TFM, ultrasonic echo energy is mainly used for imaging, but the directional nature of ultrasound phased array elements leads to differences in the energy of ultrasonic waves in different propagation directions, resulting in uneven imaging amplitudes of defects in different directions. When the beam pointing angle gradually approaches -90° and 90°, the beam directivity will slowly degenerate and the acoustic energy will progressively weaken, forming an angle blind spot for imaging. When the detection space is limited and the ultrasonic phased array transducer cannot be moved, defects within the angle blind spot will not be detected. Therefore, the paper analyzes the causes of and factors that influence the formation of ultrasonic phased array imaging angle blind spots, describes the distribution characteristics of the acoustic field radiation angle of the array element by using the solid directivity compensation factor, and constructs an ultrasonic phased array TFM algorithm based on the solid directivity compensation factor. The numerical simulation and experimental results show that when the array element width is 0.5 (\(a = 0.5\lambda\), which is commonly used in industrial detection for phased array transducers), the solid directivity compensation TFM algorithm has a better ability to compensate for the imaging amplitudes of defects in blind spots than the conventional directivity compensation TFM algorithm. When the angle blind spot is small (i.e., \(\theta_{0} = 72.3^\circ\)), the clarity of the defect imaging of the solid directivity compensation TFM algorithm is better than that of both the TFM algorithm and the conventional directivity compensation TFM algorithm. When the angle blind spot is large (i.e., \(\theta_{0} = 76.5^\circ\)), defect imaging in the angle blind spot cannot be achieved by using the TFM algorithm and the conventional directivity compensation TFM algorithm, but the solid directivity compensation TFM algorithm can achieve accurate imaging, effectively suppressing the influence of angle blind spots and expanding the detection range of ultrasonic phased arrays.

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References

  1. Kim, G., Seo, M.-K., Kim, Y.-I., Kwon, S., Kim, K.-B.: Development of phased array ultrasonic system for detecting rail cracks. Sens. Actuators A 311, Art no. 112086 (2020). https://doi.org/10.1016/j.sna.2020.112086

    Article  CAS  Google Scholar 

  2. Zhang, J., Drinkwater, B.W., Wilcox, P.D.: Effects of array transducer inconsistencies on total focusing method imaging performance. NDT and E Int. 44(4), 361–368 (2011). https://doi.org/10.1016/j.ndteint.2011.02.006

    Article  Google Scholar 

  3. Zhao, X., Ma, Z., Zhang, J.: Simplified matrix focusing imaging algorithm for ultrasonic nondestructive testing. Chin. J. Mech. Eng. 35(1), Art. No. 9 (2022). https://doi.org/10.1186/s10033-021-00637-4

    Article  Google Scholar 

  4. Yang, J., Luo, L., Yang, K., Zhang, Y.: Ultrasonic phased array sparse TFM imaging based on virtual source and phase coherent weighting. IEEE Access 8, 185609–185618 (2020). https://doi.org/10.1109/access.2020.3034122

    Article  Google Scholar 

  5. Shi, S.Q., Lin, L., Luo, Z.B., Sun, X., Jin, S.J.: Resolution enhancement of ultrasonic imaging at oblique incidence by using WTFM based on FMC-AR. Measurement (2021). https://doi.org/10.1016/j.measurement.2021.109908

    Article  Google Scholar 

  6. Holmes, C., Drinkwater, B.W., Wilcox, P.D.: Post-processing of the full matrix of ultrasonic transmit-receive array data for non-destructive evaluation. NDT and E Int. 38(8), 701–711 (2005). https://doi.org/10.1016/j.ndteint.2005.03.005

    Article  CAS  Google Scholar 

  7. Zhang, H.Y., Song, J.X., Ren, Y., Zhu, Q., Ma, X.F.: Ultrasonic imaging of wrinkles in carbon-fiber-reinforce-polymer composites. Acta Phys. Sin. 70(11), Art. No. 114301 (2021). https://doi.org/10.7498/aps.70.20210278

    Article  Google Scholar 

  8. Zhu, W., Xiang, Y., Zhang, H., Cheng, Y., Fan, G., Zhang, H.: Research on ultrasonic sparse DC-TFM imaging method of rail defects. Measurement 200, art. No. 111690 (2022). https://doi.org/10.1016/j.measurement.2022.111690

    Article  Google Scholar 

  9. Drinkwater, B.W., Bowler, A.I.: Ultrasonic array inspection of the Clifton Suspension Bridge chain-links. Insight-Non-Destr. Test. Cond. Monit. 51(9), 491–8 (2009)

    Google Scholar 

  10. Zhang, H.Y., Shao, M.T., Fan, G.P., Zhang, H., Zhu, W.F.: Detection of near-surface defects in rails combining Green’s function retrieval of ultrasonic diffuse fields and sign coherence factor imaging. Insight 62(4), 216–221 (2020). https://doi.org/10.1784/insi.2020.62.4.216

    Article  Google Scholar 

  11. Wang, Z., Xiao, Z., Li, Y., Jiang, Y.: An omnidirectional near-field comprehensive damage detection method for composite structures. Appl. Sci. Basel 9(3), Art. 567 (2019). https://doi.org/10.3390/app9030567

    Article  CAS  Google Scholar 

  12. Zhang, M.K., Fan, G.P., Zhu, W.F.: Multi-defect detection based on ultrasonic Lamb wave sign phase coherence factor imaging method. Insight 63(11), 659–666 (2021). https://doi.org/10.1784/insi.2021.63.11.659

    Article  Google Scholar 

  13. Zhu, W.-F., Fan, G.-P., Meng, X.-Z.: Ultrasound SAFT imaging for HSR ballastless track using the multi-layer sound velocity model. Insight 63(4), 199–208 (2021). https://doi.org/10.1784/insi.2020.63.4.199

    Article  Google Scholar 

  14. Sun, Y., Yuan, S., Qiu, L., Cai, J., Wang, Q.: Structural health monitoring based on lamb wave phased array and image enhancement. Acta Aeronaut. Astronaut. Sin. 30(7), 1325–30 (2009)

    Google Scholar 

  15. Yu, L., Giurgiutiu, V.: Design, implementation, and comparison of guided wave phased arrays using embedded piezoelectric wafer active sensors for structural health monitoring. In: Proceedings of SPIE—The International Society for Optical Engineering, vol. 6173, pp. 61731M-61731M-12 (2006). https://doi.org/10.1117/12.658646.

  16. Wandowski, T., et al.: Embedded damage localization subsystem based on elastic wave propagation. Comput. Aided Civ. Infrastructure Eng. (2015). https://doi.org/10.1111/mice.12144

    Article  Google Scholar 

  17. Yu, L., Giurgiutiu, V.: In situ 2-D piezoelectric wafer active sensors arrays for guided wave damage detection. Ultrasonics 48(2), 117–134 (2008). https://doi.org/10.1016/j.ultras.2007.07.008

    Article  PubMed  Google Scholar 

  18. Yao, C., et al.: Sparse array ultrasonic lamb wave TDTE imaging method. IEEE Sens. J. 21(18), 20910–20920 (2021). https://doi.org/10.1109/jsen.2021.3109118

    Article  ADS  Google Scholar 

  19. Wang, Z., Liu, T., Wu, X., Liu, C.: Application of an oversampling method based on GMM and boundary optimization in imbalance-bearing fault diagnosis. IEEE Trans. Ind. Inform. (2023). https://doi.org/10.1109/tii.2022.3167386

    Article  Google Scholar 

  20. Zhang, B., Xie, F., Dong, H., Gong, J.: Ultrasonic guided wave focusing by a generalized phased array. Acoust. Phys. 59(1), 97–102 (2013). https://doi.org/10.1134/s1063771013010146

    Article  ADS  Google Scholar 

  21. Dai, Y., Yan, S., Zhang, B.: Acoustic field excited by single force with arbitrary direction in semi-infinite elastic space. Acoust. Phys. 65(3), 235–245 (2019). https://doi.org/10.1134/s1063776119030197

    Article  ADS  Google Scholar 

  22. Drinkwater, B.W., Wilcox, P.D.: Ultrasonic arrays for non-destructive evaluation: a review. NDT and E Int. 39(7), 525–541 (2006). https://doi.org/10.1016/j.ndteint.2006.01.010

    Article  CAS  Google Scholar 

  23. Selfridge, A.R., Kino, G.S., Khuri-Yakub, B.T.: A theory for the radiation pattern of a narrow-strip acoustic transducer. Appl. Phys. Lett. 37(1), 35–36 (1980). https://doi.org/10.1063/1.92075

    Article  ADS  CAS  Google Scholar 

  24. Schmmer, L.W.: Fundamentals of ultrasonic phased arrays. Mod. Phys. Lett. B 22(11), 917–921 (2008). https://doi.org/10.1142/s0217984908015905

    Article  ADS  CAS  Google Scholar 

  25. Li, R., Ni, Q.Q., Xia, H., Natsuki, T.: Analysis of individual attenuation components of ultrasonic waves in composite material considering frequency dependence. Composite B 140, 232–240 (2018). https://doi.org/10.1016/j.compositesb.2018.02.044

    Article  Google Scholar 

  26. Miller, P.H.G.F.: The field and radiation impedance of mechanical radiators on the free surface of a semi-infinite isotropic solid. Proc. R. Soc. Lond. Ser. A. 223(1155), 521–541 (1997). https://doi.org/10.1098/rspa.1954.0131

    Article  ADS  MathSciNet  Google Scholar 

  27. Wilcox, P.D., Holmes, C., Drinkwater, B.W.: Advanced reflector characterization with ultrasonic phased arrays in NDE applications. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 54(8), 1541–1550 (2007). https://doi.org/10.1109/TUFFC.2007.438

    Article  PubMed  Google Scholar 

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Acknowledgements

This research was funded by the National Key Research and Development Program of China (Grant No. 2022YFF0605604), the National Natural Science Foundation of China (Grant Nos. 12004240, 12025403, 12104290,12304514 and 12174245), and the China Postdoctoral Science Foundation (Grant No. 2020M671022).

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Authors and Affiliations

  1. School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, 201620, China

    ChunXiang Gao, WenFa Zhu, GuoPeng Fan & Hui Zhang

  2. School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China

    WenFa Zhu, YanXun Xiang, GuoPeng Fan & Hui Zhang

  3. Shanghai Key Laboratory of Intelligent Sensing and Detection Technology, Shanghai, 200237, China

    YanXun Xiang

  4. School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China

    HaiYan Zhang

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  1. ChunXiang Gao
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Contributions

CG proposed the idea, performed the numerical simulations, and wrote the manuscript; WZ performed the experimental setup and reviewed and edited the manuscript; GF and HZ performed the theoretical calculation and analysis through constructive discussions; and YX and HZ participated in technical discussions and supervision. All authors contributed to manuscript revision and approved the submitted version.

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Correspondence to WenFa Zhu or YanXun Xiang.

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Gao, C., Zhu, W., Xiang, Y. et al. Ultrasonic Phased Array Imaging for Defects in Angle Blind Spots Based on the Solid Directivity Function. J Nondestruct Eval 43, 26 (2024). https://doi.org/10.1007/s10921-023-01040-x

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