An algorithm evaluates phase velocity in dispersive lamb waves, highlighting improved accuracy and efficiency.
This study introduces an automated computational tool to evaluate the phase velocity of the highly dispersive A0 mode using only two signals measured along the wave propagation path. The algorithm combines the zero-crossing technique with automated spectral decomposition, utilizing a bank of bandpass filters with adaptive bandwidths. Validated through theoretical and experimental analysis of an aluminium plate near 300 kHz, the results demonstrate that using a two-signal set and variable filter widths significantly improves accuracy and extends the measurable frequency range of the dispersion curve. Experimental results demonstrate that by applying various filter widths, the phase velocity dispersion curve segment can be reconstructed over a frequency range exceeding 65% of the signal’s spectral width at the −40 dB level. The reconstruction yielded an average relative error of 0.8% ± 1.2%, while the best-case scenario showed an error of just 0.3% ± 0.4%. Implementing automated filter parameter selection on a signal pair offers a time-efficient alternative to traditional spatial scanning, significantly simplifying data collection while reducing labour and time requirements.
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Draudvilienė et al. (2026) studied this question.
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