Characterization of impact damage in composite laminates using guided wavefield imaging and local wavenumber domain analysis

► We present a method of analyzing guided wavefield data for the purpose of characterizing damage in composite laminates. ► Local wavenumber is measured throughout the wavefield. ► Performance of the method is evaluated as applied to numerical data. ► Wavenumber measurements of experimental wavefields show good agreement with theory. ► Non-contact measurement of wavenumber permits characterization of delamination depth in composite laminates. Delaminations in composite laminates resulting from impact events may be accompanied by minimal indication of damage at the surface. As such, inspections are required to ensure defects are within allowable limits. Conventional ultrasonic scanning techniques have been shown to effectively characterize the size and depth of delaminations but require physical contact with the structure and considerable setup time. Alternatively, a non-contact scanning laser vibrometer may be used to measure guided wave propagation in the laminate structure generated by permanently bonded transducers. A local Fourier domain analysis method is presented for processing guided wavefield data to estimate spatially dependent wavenumber values, which can be used to determine delamination depth. The technique is applied to simulated wavefields and results are analyzed to determine limitations of the technique with regards to determining defect size and depth. Based on simulation results, guidelines for application of the technique are developed. Finally, experimental wavefield data is obtained in quasi-isotropic carbon fiber reinforced polymer (CFRP) laminates with impact damage. The recorded wavefields are analyzed and wavenumber is measured to an accuracy of up to 8.5% in the region of shallow delaminations. These results show the promise of local wavenumber domain analysis to characterize the depth of delamination damage in composite laminates. The technique can find application in automated vehicle health assurance systems with potential for high detection rates and greatly reduced operator effort and setup time.