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 …

Bridges play a crucial role in modern societies, regardless of their culture, geographical
location, or economic development. The safest, economical, and most resilient bridges are …

This paper deals with state of the art in structural health monitoring (SHM) methods in
offshore and marine structures. Most SHM methods have been developed for onshore …

Over the last two decades, the integration of big data and deep learning technologies has
demonstrated remarkable effectiveness across various domains of civil engineering, leading …

Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …

Abstract In Structural Health Monitoring (SHM), measured data that correspond to an
extensive set of operational and damage conditions (for a given structure) are rarely …

Data-driven machine-learning algorithms generally suffer from a lack of labelled health-state
data, mainly those referring to damage conditions. To address such an issue, population …

With the increased use of composites in aircraft, many new successful contributions to the
advancement of the structural health monitoring (SHM) field for composite aerospace …

Classifiers based on machine learning algorithms trained through hybrid strategies have
been proposed for structural health monitoring (SHM) of bridges. Hybrid strategies use …

The maintenance and repair of bridges (and other large scale infrastructure projects) is a
major area which could benefit from Structural Health Monitoring technology. Inspections on …