This paper aims to review high-dimensional data analytic (HDDA) methods for structural
health monitoring (SHM) and non-destructive evaluation (NDE) applications. High …

In the field of structural health monitoring (SHM), the sensor measurement signals collected
from the structure are the foundation and key of the SHM system. However, the loss of …

In the application of structural health monitoring, the measured data might be temporarily or
permanently lost due to sensor fault or transmission failure. The measured data with a high …

In structural health monitoring (SHM) systems, data loss inevitably occurs and reduces the
applicability of SHM techniques, such as condition assessment and damage identification …

Reconstruction of lost responses under external loads, eg ambient and seismic loading
conditions, is important for structural health monitoring to evaluate the safety of structures …

Abstract Machine learning brings a new paradigm to the traditional structural modal
parameter identification problem. In this study, we propose a novel machine learning …

This article proposes a novel dynamic response reconstruction approach for structural
health monitoring using densely connected convolutional networks. Skip connection and …

In the last decades, the majority of the existing infrastructure heritage is approaching the end
of its nominal design life mainly due to aging, deterioration, and degradation phenomena …

Artificial Intelligence applied to Structural Health Monitoring (SHM) has provided
considerable advantages in the accuracy and quality of the estimated structural integrity …

The main challenge in the implementation of long-lasting vibration monitoring systems is to
tackle the constantly evolving complexity of modern “mesoscale” structures. Thus, the design …