Laser ultrasonic wave spatial gradient features for damage detection

Laser ultrasonic wave spatial gradient features for damage detection

Zihan Wu, Michael D. Todd

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Abstract. This work presents a damage imaging method exploiting full-field guided ultrasonic waves excited by a thermoelastic-effect laser. From the high spatial resolution data produced, a spatial gradient–based image processing technique was developed using gradient vectors to extract features sensitive to defects. Localized mechanical impedance changes in the damaged area induce a local distortion of the waveform, which was quantified by the variation of the gradient vectors in the scanning area as time evolves. Such variation was accumulated over time with an analytically derived optimal statistical threshold filter to generate a gradient-orientation map for damage imaging. The proposed algorithm is shown to detect distinctive damage patterns when tested experimentally on a 3 mm aluminum plate with multiple simultaneous simulated defects. Compared to conventional techniques like local wavenumber estimation, the generation of the accumulated orientation map involves no filtering process in the frequency or wavenumber domain, but it comes at the expense of less accurate shaping of the defect. A spatial covariance analysis was adopted to locate damage from the results as well as to evaluate the correlation among different kinds of defects.

Laser Ultrasonics, Spatial Gradient, Covariance, Ultrasonic Imaging

Published online 3/30/2023, 8 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Zihan Wu, Michael D. Todd, Laser ultrasonic wave spatial gradient features for damage detection, Materials Research Proceedings, Vol. 27, pp 76-83, 2023


The article was published as article 10 of the book Structural Health Monitoring

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

[1] J. L. Rose, A vision of ultrasonic guided wave inspection potential, Proceedings of the 7th ASME NDE Tropical Conference-2001, San Antonio, USA (2001), 1-22.
[2] J. L. Rose, The upcoming revolution in ultrasonic guided waves, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2011, Int. Society for Optics and Photonics vol. 7983 (2011), 798302.
[3] F. G. Yuan, Structural Health Monitoring (SHM) in Aerospace Structures, Woodhead, Cambridge, 2016.
[4] C. C. Chia, J. R. Lee, and C. Y. Park, Radome health management based on synthesized impact detection, laser ultrasonic spectral imaging, and wavelet-transformed ultrasonic propagation imaging methods, Composites Part B: Engineering 43(8) (2012) 2898–2906.
[5] J. R. Lee et al., Laser ultrasonic propagation imaging method in the frequency domain based on wavelet transformation, Optics and Lasers in Engineering 49(1) (2011), 167–175.
[6] H. Sohn et al., Delamination detection in composites through guided wave field image processing Composites Science and Technology 71(9) (2011), 1250–1256.
[7] Z. Tian and L. Yu, Lamb wave frequency–wavenumber analysis and decomposition, Journal of Intelligent Material Systems and Structures 25(9) (2014), 1107–1123.
[8] H. Y. Chang and F. G. Yuan, Damage imaging in a stiffened curved composite sandwich panel with wavenumber index via Riesz transform, Structural Health Monitoring 19(3) (2020), 902–916.
[9] J. B. Harley and C. C. Chia, Statistical partial wavefield imaging using lamb wave signals, Structural Health Monitoring 17(4) (2018), 919–935.
[10] B. Park, H. Sohn, and P. Liu, Accelerated noncontact laser ultrasonic scanning for damage detection using combined binary search and compressed sensing, Mechanical Systems and Signal Processing 92 (2017), 315–333.
[11] S. Y. Chong and M. D. Todd, Dispersion curve estimation via a spatial covariance method with ultrasonic wavefield imaging, Ultrasonics 89 (2018), 46–63.
[12] E. B. Flynn et al., Structural imaging through local wavenumber estimation of guided waves, NDT & E International 59 (2013), 1–10.
[13] Z. Wu, S. Y. Chong, and M. D. Todd, Laser ultrasonic imaging of wavefield spatial gradients for damage detection, Structural Health Monitoring 20(3) (2021), 960-977.
[14] S. P. Liou and R. C. Jain, Motion detection in spatiotemporal space. Computer Vision, Graphics, and Image Processing 42(2) (1989), 227–250.