Power, Control, and Data Processing Systems

Power, Control, and Data Processing Systems

Adaptive Beamforming for Improved Ultrasonic Imaging in Noisy Environments

Document Type : Original Research

Author
Mehdi Bekrani
Khodakakram Blvd.
10.30511/pcdp.2024.719229
Abstract
In this paper, we introduce a novel Delay-Weight-Sum (DWS) beamforming technique for defect detection in non-destructive testing (NDT). This method offers improved accuracy over traditional Total Focusing Method (TFM) and its weighted variants. The proposed technique enhances defect detection and imaging quality through an advanced DWS beamforming approach based on a minimum variance method. The minimum variance approach utilizes the Newton-Schulz iterative method for efficient matrix inverse approximation. Additionally, a new non-linear weighting mechanism, based on a sigmoid function, is introduced to refine the matrix inverse approximation for DWS beamforming. This mechanism dynamically adjusts the weighting to enhance reflective points while reducing background noise. Comparative analyses demonstrate the superior imaging resolution and reduced background noise achieved by the proposed method compared to existing TFM-based techniques. Despite its computational demands, simulation results show that the method significantly improves ultrasonic image quality and contrast, holding promise for advancements in ultrasonic NDT, especially in heterogeneous and noisy environments.
Keywords
Ultrasonic imaging
Ultrasonic phased array
Beamforming
Total focusing method
Minimum Variance
Subjects
[1] L. W. Schmerr, An ultrasonic system, in Fundamentals of Ultrasonic Nondestructive Evaluation, Springer, pp. 1-13, 2016.
[2] Olympus NDT, Introduction to phased array ultrasonic technology applications: D Tech Guideline, Olympus NDT, 2004.
[3] M. Jobst and G. Connolly, Demonstration of the Application of the Total Focusing Method to the Inspection of Steel Welds, European Conference on Non-Destructive Testing, pp. 1-11, 2010.
[4] C. Holmes, B. W. Drinkwater, and P. D. Wilcox, Post-processing of the full matrix of ultrasonic transmit-receive array data for non-destructive evaluation, NDT & E International, vol. 38, no.8, pp. 701-711, 2005.
[5] B. W. Drinkwater and P. D. Wilcox, Ultrasonic arrays for non-destructive evaluation: A review, NDT & E International, vol. 39, no. 7, pp. 525-541,2006.
[6] J. Lambert, A. Pédron, G. Gens, F. Bimbard, L.Lacassagne, and E. Lakovleva, Performance evaluation of total focusing method on GPP and GPU, Conference on Design and Architectures for Signal and Image Processing (DASIP), pp. 1-8, 2012.
[7] L. Jeune, S. Robert, P. Dumas, A. Membre, and C. Prada, Adaptive Ultrasonic Imaging with the Total Focusing Method for Inspection of Complex Components Immersed in Water, AIP Conference Proceedings, vol. 1650, pp. 1037-1046, 2015.
[8] C. Huang and F. Lanza di Scalea, Application of sparse synthetic aperture focusing techniques to ultrasound imaging in solids using a transducer wedge, IEEE Trans. Ultrason., Ferroelectr., Freq.Control, vol. 71, no. 2, pp. 280-294, Feb. 2024.
[9] X. Yang, E. Verboven, B.-F. Ju, and M. Kersemans, Comparative study of ultrasonic techniques for reconstructing the multilayer structure of composites, "NDT E Int., vol. 121, no. 102460, Jul.2021.
[10] A. Velichko, E. L. Villaverde, and A. J. Croxford, Local scattering ultrasound imaging," Sci. Rep., vol. 11, no. 1, p. 993, Jan. 2021.
[11] H. Shi, M. Ebrahimi, P. Zhou, K. Shao, and J. Li, Ultrasonic and phased-array inspection in titanium-based alloys: A review," Proc. Inst. Mech.Eng., Part E, J. Process Mech. Eng., vol. 237, no.2, pp. 511-530, Apr. 2023.
[12] Chandler, M. G., Croxford, A. J., and Wilcox, P.D., A Multivariate Statistical Approach to Wrinkling Detection in Composites," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 71, no. 9, pp. 1141-1151, 2024.
[13] P. Shen, Y. Wu, Z. Luo, Z. Wu, J. Jing, and H. Zhang, Advanced Orthogonal Frequency and Phase Modulated Waveform for Ultrasonic Phased Array TFM Detection in CFRP Composites, "IEEE Transactions on Instrumentation and Measurement, vol. 73, no. 4504410, pp. 1-10, 2024.
[14] L. P. Piedade, G. Painchaud-April, A. Le Du, and P. Bélanger, Compressive Sensing Strategy on Sparse Array to Accelerate Ultrasonic TFM Imaging," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 70, no. 6, pp 538-550, June 2023.
[15] B. Gauthier, G. Painchaud-April, A. Le Du, and P. Bélanger, Lightweight and Amplitude-Free Ultrasonic Imaging Using Single-Bit Digitization and Instantaneous Phase Coherence," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 69, no. 5, pp. 1763-1774, May 2022.
[16] Y. -X. Qin, X. -M. Xiong, Y. Chen, and Y. Wang, Optimization Research on Defect Localization in Ultrasonic Images of Anisotropic and Multilayer CFRP Structures," IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-14,2024.
[17] E. Nicolson, D. Lines, E. Mohseni, and C. N.MacLeod, Single-Bit Reception With Coded Excitation for Lightweight Advanced Ultrasonic Imaging Systems," IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 71, no.9, pp. 1120-1131, Sept. 2024.
[18] W. Zhu et al., Sparse Optimal Design of an Ultrasonic Sensor Array for Fast TFM Based on a Discrete Slime Mold Algorithm," IEEE Sensors Journal, vol. 24, no. 8, pp. 12207-12216, April 2024.
[19] M. Li and G. Hayward, Ultrasound Nondestructive Evaluation (NDE) Imaging with Transducer Arrays and Adaptive Processing, Sensors, vol. 12, no. 1, pp. 42-54, 2012.
[20] S. M. Sakhaei, A decimated minimum variance beamformer applied to ultrasound imaging, Ultrasonics, vol. 59, 2015.
[21] M. Ehsani, M. Bekrani, and S. Garousi, Robust Beamforming for Ultrasonic Imaging using Wavelet-based Thresholding and Coherence Weighting," International Journal of Industrial Electronics Control and Optimization, vol. 7, no. 4, pp 339-350, 2024.
[22] M. Li and G. Hayward, Adaptive Array Processing for Enhanced Ultrasonic Non-destructive Evaluation(NDE) and Imaging, Proceedings of the American Institute of Physics (AIP) Conference, vol. 2102, pp. 100007/1-100007/8, May 2019.
[23] S.-L. Pu, H. Guo, H.-W. Xie, C. Chen, P. Zhou, and G.-Q. Zhou, Minimum Variance Optimizations With Different Covariance Matrices in PlaneWave Ultrasound Imaging," IEEE Transactions on Instrumentation and Measurement, vol. 73, no.4509213, pp. 1-13, 2024.
[24] Y. Wang, S. Feng, J. Pan, C. Zheng, H. Peng, and Y. Wang, Random Matrix Theory-Based Wiener Post-filter Combined With Eigenspace and Spatial Coherence-Based Minimum Variance Beamformer for Coherent Plane-Wave Adaptive Compounding, "IEEE Transactions on Instrumentation and Measurement, vol. 73, no. 4503317, pp. 1-17, 2024.
[25] O. M. H. Rindal, J. P. Asen, S. Holm, and A.Austeng, Understanding contrast improvements from capon beamforming, in Proc. IEEE Int. Ultrason. Symp., pp. 1694-1697, 2014.
[26] K. Diamantis, A. Greenaway, T. Anderson, J.A. Jensen, and V. Sboros, Experimental performance assessment of the sub-band minimum variance beamformer for ultrasound imaging, Ultrasonics, vol. 79, pp. 87-95, Aug. 2017.
[27] B. M. Asl and A. Mahloojifar, Eigenspace-based minimum variance beamforming applied to medical ultrasound imaging, IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 57, no. 11, pp.2381-2390, Nov. 2010.
[28] H. Hasegawa and R. Nagaoka, Improvement of performance of minimum variance beamformer by introducing cross covariance estimate, J. Med. Ultrason., vol. 47, no. 2, pp. 203-210, Apr. 2020.
[29] Z. Zhang, Z. Lei, M. Zhou, H. Hasegawa, and S. Gao, Complex-valued convolutional gated recurrent neural network for ultrasound beamforming, IEEE Trans. Neural Netw. Learn. Syst., doi:10.1109/TNNLS.2024.3384314.
[30] S. Goudarzi, A. Basarab, and H. Rivaz, A unifying approach to inverse problems of ultrasound beamforming and deconvolution, IEEE Trans.Comput. Imaging, vol. 9, pp. 197-209, 2023.
[31] K. Kim, S. Park, J. Kim, S. B. Park, and M. Bae, A fast minimum variance beamforming method using principal component analysis, IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 61, no. 6, pp 930-945, Jun. 2014.
[32] M. Bae, S. B. Park, and S. J. Kwon, Fast minimum variance beamforming based on Legendre polynomials, IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 63, no. 9, pp. 1422-1431, Sep.2016.
[33] S. Goudarzi, A. Asif, and H. Rivaz, Planewave ultrasound beamforming through independent component analysis, Comput. Methods Programs Biomed., vol. 203, 2021, Art. no. 106036,2021.
[34] M. Sutclie, M. Weston, B. Dutton, and I.Cooper, Real-Time Full Matrix Capture with Auto-Focusing of Known Geometry through Dual-Layered Media, NDT & E International, vol. 51,2012.Adaptive Beamforming for Improved Ultrasonic Imaging in Noisy EnvironmentsPOWER, CONTROL AND DATA PROCESSING SYSTEMS - Vol 1(1), 2024Page | 10
[35] M. J. Simões, F. Santos, and J. B. Santos, FPGABased Control System of an Ultrasonic Phased Array, Journal of Mechanical Engineering, vol. 57,no. 2, 2011.
[36] D. DasGupta, In-place matrix inversion by modified Gauss-Jordan algorithm, Applied Mathematics, vol 4, pp. 1392-1396, 2013.
[37] Strang, G., Introduction to Linear Algebra, (4th), Wellesley-Cambridge Press, 2009.
[38] M. Bekrani and V. H. Vaghef, A Novel Method for Imaging and Defect Detection Using Ultrasonic Phased Arrays," Iranian Conference on Mathematical Physics, Qom University of Technology, November 2016.
[39] M. Bekrani and V. H. Vaghef, Ultrasound PhasedArray Imaging with Minimum Variance-Based Beamforming," The 11th Iranian and the 1st International Conference on Machine Vision and Image Processing (MVIP 2020), 2020.
[40] N. J. Higham, Iterative Refinement for the Solution of Perturbed Linear Systems," SIAM Journal on Matrix Analysis and Applications, vol. 18, no.4, pp. 1035-1051, 1997.
[41] N. J. Higham, Accuracy and Stability of Numerical Algorithms, SIAM Publications, 2002.
[42] G. H. Golub and C. F. Van Loan, Matrix Computations, Johns Hopkins University Press, 2013.
Power, Control, and Data Processing Systems
Volume 1, Issue 1
Autumn 2024
Pages 40-49

  • Receive Date 09 November 2024
  • Revise Date 20 November 2024
  • Accept Date 23 November 2024
  • First Publish Date 01 December 2024
  • Publish Date 01 December 2024