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A Lamb Wave Wavenumber-Searching Method for a Linear PZT Sensor Array.

Bin Liu1,2, Tingzhang Liu3, Jianfei Zhao4

  • 1School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China. khqlb@shu.edu.cn.

Sensors (Basel, Switzerland)
|September 28, 2019
PubMed
Summary

A new wavenumber-searching method accurately determines Lamb wave signals, even with undersampling. This technique improves damage localization in materials like aluminum and composites.

Keywords:
Lamb waveStructural health monitoringlinear PZT sensor arraywavenumber

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Area of Science:

  • Materials Science
  • Non-Destructive Testing
  • Wave Propagation

Background:

  • Lamb wave-based structural health monitoring (SHM) is crucial for detecting damage in composite materials.
  • Accurate wavenumber determination is essential for reliable Lamb wave signal analysis.
  • Existing methods face challenges with signals not meeting the Nyquist sampling theorem.

Purpose of the Study:

  • To propose a novel wavenumber-searching method for Lamb wave array signals.
  • To address limitations of traditional methods, particularly with undersampled data.
  • To validate the method's effectiveness for damage localization.

Main Methods:

  • A time-domain compensation technique is employed to convert time-domain signals to spatial sampling signals.
  • The method utilizes Morlet wavelet fitting to minimize errors in wavenumber estimation.
  • The process involves converting 2D time-spatial data to 1D synthesized spatial data.

Main Results:

  • The proposed method successfully obtains the wavenumber of Lamb wave array signals, even when the spatial sampling rate is below the Nyquist limit.
  • Wavenumber errors were found to be within 2.2 rad/m on 2024-T3 aluminum alloy.
  • Damage localization on a carbon fiber composite laminate plate showed a maximum error of 2.11 cm.

Conclusions:

  • The developed wavenumber-searching method is effective for analyzing Lamb wave signals with undersampled spatial rates.
  • This technique enhances the accuracy of damage localization in composite structures.
  • The method offers a robust solution for SHM applications in materials science.