Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …

Concrete structures have emerged as some of the most extensively utilized materials in the
construction industry due to their inherent plasticity and high-strength characteristics …

Accuracy metrics have been widely used for the evaluation of predictions in machine
learning. However, the selection of an appropriate accuracy metric for the evaluation of a …

This paper introduces two deep learning approaches to localize acoustic emissions (AE)
sources within metallic plates with geometric features, such as rivet-connected stiffeners. In …

This paper introduces a deep learning-based framework to localize and characterize
acoustic emission (AE) sources in plate-like structures that have complex geometric …

Acoustic emission (AE) localization plays an important role in the prediction and control of
potential hazardous sources in complex structures. However, existing location methods …

Interest in damage mode classification of composite structures by Acoustic Emission (AE)
inspection technique and clustering analysis by machine learning has been increasingly …

This review introduces several areas of importance in acoustic emission (AE) technology,
starting from signal attenuation. Signal loss is a critical issue in any large-scale AE …

Fretting fatigue can significantly reduce the life of components, leading to unexpected in-
service failures. This phenomenon has been studied for over a century, with significant …

An acoustic emission (AE) approach for non-destructive evaluation of structures has been
developed over the last two decades. In complex structures, one of the limitations of AE …