Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …

This article proposes a novel probabilistic machine learning method based on unsupervised
novelty detection for health monitoring of civil structures. The core of this method is based on …

Abstract Machine learning has become an influential and useful tool for many civil
engineering applications, particularly structural health monitoring (SHM). For this reason …

Condition monitoring of industrial equipment, combined with machine learning algorithms,
may significantly improve maintenance activities on modern cyber-physical production …

This article proposes an innovative unsupervised learning method for early damage
detection and long‐term structural health monitoring of civil structures under environmental …

Modal frequencies are widely used for vibration‐based structural health monitoring (SHM)
and for capturing the dynamics of a monitored structure to reveal possible failures. However …

Environmental variability is still a major challenge in structural health monitoring. Due to the
similarity of changes caused by environmental variations to damage, false positive and false …

In the age of the smart city, things like the Internet of Things (IoT) and big data analytics are
making big changes to the way traditional structural health monitoring (SHM) is done. Also …

Early damage detection is an initial step of structural health monitoring. Thanks to recent
advances in sensing technology, the application of data-driven methods based on the …