Damage Localization in 3D-Printed Plates with Different Infill Densities

The growth in the use of additive manufacturing techniques for prototypes and industrial components implies the need to find robust and reliable tools for damage detection, localization, size estimation, and identification. This study focuses on guided-wave propagation in 3D-printed components and their sensitivity to damage. The material under investigation is 3D-printed poly(lactic acid) (PLA), which was used to manufacture flat plates. Several plates were prepared with varying infill densities. Lower infill density allows to save printing material, but it influences the guided-wave propagation behavior. To study the damage localization capability, plates with and without internal artificial defects were prepared. For each infill density, a healthy and a damaged plate were prepared. The guided waves were excited in the plates using surface-mounted piezoelectric transducers, while the sensing was realized by a scanning laser Doppler vibrometer. Five-cycle-long tone-burst excitation signals of different central frequencies were used, for comparison, where it was demonstrated that lowering the plate's infill density results in the appearance of higher-order modes at lower cut-off frequencies. Additionally, it was shown that guided-wave-based imaging can reveal hidden flaws and even the inner structure of 3D-printed polymers. This shows the good potential of guided-wave-based techniques for the structural health monitoring of 3D-printed structures.