The birth of smart materials such as piezoelectric (PZT) transducers has aided in
revolutionizing the field of structural health monitoring (SHM) based on non-destructive …

Structural health monitoring (SHM) is the continuous on-board monitoring of a structure's
condition during operation by integrated systems of sensors. SHM is believed to have the …

This paper reports on a novel metamodel for impact detection, localization and
characterization of complex composite structures based on Convolutional Neural Networks …

Common damages in concrete materials and structures are usually in small sizes at initial
stage, which induce small stiffness and mass loss being difficult to evaluate severity level …

Deep learning approach using convolutional neural networks (CNNs) has ushered in
numerous breakthroughs in image-based recognition field, but the electromechanical …

Preliminaries convolutional neural network (CNN) applications have recently emerged in
structural health monitoring (SHM) systems focusing mostly on vibration analysis. However …

Composite materials have been widely used in many industries due to their excellent
mechanical properties. It is difficult to analyze the integrity and durability of composite …

For the first time, this paper proposed a simple two-dimensional convolutional neural
network (2-D CNN) integrated with electromechanical admittance (EMA, inverse of …

Local stress concentration occurs when faults are present in pipelines under pressure. An
example of such defects is the problem of corrosion caused by the environment in the field of …

High-frequency electromechanical impedance measured from the piezoelectric transducer
has been recognized as an effective indicator to infer minor damage occurrence. Over the …