The analysis of ultrasonic NDE data has traditionally been addressed by a trained operator
manually interpreting data with the support of rudimentary automation tools. Recently, many …

Bayesian inference provides a powerful approach to system identification and damage
assessment for structures. The application of Bayesian method is motivated by the fact that …

This paper presents the development of a robust automatic damage diagnosis technique
that uses ultrasonic Lamb waves and a deep autoencoder (DAE) to detect and classify …

Ultrasonic guided waves (UGW) are widely used in structural health monitoring (SHM)
systems due to the sensitivity of their propagation mechanisms to local material changes, ie …

SHM methods for damage detection and localization in plate-like structures have typically
relied on signal post-processing techniques applied to ultrasonic guided-waves. The time of …

This paper proposes a deep learning framework for artefact identification and suppression in
the context of non-destructive evaluation. The model, based on the concept of autoencoders …

The effect of the adhesive geometry on the impact damage of adhesively bonded aluminum
sandwich panels was studied experimentally and numerically. Both the physical testing and …

Abstract Ultrasonic Guided Waves (GW) actuated by piezoelectric transducers installed on
structures have proven to be sensitive to small structural defects, with acquired scattering …

This paper proposes the use of a physics-based Bayesian framework for the localization and
identification of damage in composite beam structures using ultrasonic guided-waves. The …

This paper proposes a new damage index named degree of health (DoH) to efficiently tackle
structural damage monitoring in real-time. As a key contribution, the proposed index relies …