The Capability Assessment of the Spectrum Decomposition Technique for Measurements of the Group Velocity of Lamb Waves

  • Lina Draudviliene
  • Asta Meskuotiene
  • Renaldas Raisutis
  • Hacene Ait-Aider


The ultrasonic guided waves are dispersive waves characterized by the phase and group velocities dispersion curves. In order to use guided waves in various industrial applications, their parameters must be known. Since these guided wave velocities depend on the frequency and thickness of the material, they propagate differently comparing to bulk ultrasonic waves. Therefore, to analyze the parameters of such waves, new measurement techniques should be proposed and possibilities of their application have to be investigated. In this paper possibilities to measure the group velocity based on the spectrum decomposition approach are presented. The investigations are carried out using the simulated and experimental signals of Lamb wave propagating in a 2 mm thickness aluminium plate. The two fundamental modes \(\hbox {A}_{0}\) and \(\hbox {S}_{0}\) are selected. Using the proposed technique, segments of the group velocity dispersion curves have been reconstructed and compared with the dispersion curves calculated by the SAFE method to estimate errors. Accordingly to the obtained lower absolute and relative errors, an optimal set of narrowband filters with bandwidth from 20 kHz up to 100 kHz for the \(\hbox {A}_{0}\) mode and from 80 kHz up to 160 kHz for the \(\hbox {S}_{0}\) mode are proposed. Applying the proposed optimal frequency sets of narrowband filters for the experimental signals, segments of the group velocity dispersion curves for both modes are reconstructed. The average relative error for the \(\hbox {A}_{0}\) mode is 1.7–2.2% (expanded relative uncertainty ± (2.2–2.8)%) and 0.78–1.2% (expanded relative uncertainty ± (0.5–0.8)%) for the \(\hbox {S}_{0}\) mode.


Lamb wave Dispersion curves Group velocity Spectrum decomposition technique Uncertainty 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Lina Draudviliene
    • 1
  • Asta Meskuotiene
    • 2
  • Renaldas Raisutis
    • 1
  • Hacene Ait-Aider
    • 3
  1. 1.Kaunas University of TechnologyUltrasound Research InstituteKaunasLithuania
  2. 2.Kaunas University of TechnologyMetrology InstituteKaunasLithuania
  3. 3.Mouloud Mammeri University of Tizi-OuzouTizi OuzouAlgeria

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