A guided wave simulation method for layered composites based on the wave and finite element scheme is presented. An approach for calculating complex displacement fields such as those generated from piezoelectric transducers is developed. The scattering of waves from different types of defects is computed. A rigorous energy based criteria is proposed for model order reduction. All calculations are carried out in the frequency domain and an inverse discrete fourier transform is performed to get the time domain result.Numerical examples of a multi-layered composite beam are performed to assess the performance and validate the methodology. Three types of damages are simulated namely a notch, a transverse crack and an internal delamination. The results are validated against finite element simulations and are found to be in excellent agreement. Moreover the approach is found to be orders of magnitude faster compared to finite element simulations.

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The development of reliable structural health monitoring techniques is enabling a healthy transition from preventive to condition-based maintenance, hence leading to safer and more efficient operation of different industries. Ultrasonic guided-wave based beamforming is one of the most promising techniques, which supports the monitoring of large thin-walled structures. However, beamforming has been typically applied to the post-processing stage (also known as virtual or receiver beamforming) because transmission or physical beamforming requires complex hardware configurations. This paper introduces an electronic structural health monitoring system that carries out transmission beamforming experiments by simultaneously emitting and receiving ultrasonic guided-waves using several transducers. An empirical characterization of the transmission beamforming technique for monitoring an aluminum plate is provided in this work. The high signal-to-noise ratio and accurate angular precision of the physical signal obtained in the experiments suggest that transmission beamforming can increase the reliability and robustnessof this monitoring technique for large structures and in real-world noisy environments.