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 …

Wind energy is one of the most important renewable energy sources and many countries are
predicted to increase wind energy portion of their whole national energy supply to about …

This paper presents four kernel-based algorithms for damage detection under varying
operational and environmental conditions, namely based on one-class support vector …

With recent ground-breaking advances, machine learning (ML) has been applied widely in
numerous fields in this day and age. However, because of the application of …

The aim of this article is to propose novel damage indices for damage localization and
quantification based on time series modeling. In order to extract damage-sensitive features …

Abstract In the Structural Health Monitoring of bridges, the effects of the operational and
environmental variability on the structural responses have posed several challenges for …

This study focused on the development of damage detection indices using unsupervised
Machine Learning with data obtained from tests of a full-scale bridge deck mock-up …

To address the issue faced by phase space trajectory (PST) based methods for identifying
structural damage using high dimensional dynamic responses of structures under stochastic …

This paper describes the backgrounds, motivations and recent history of structural health
monitoring (SHM) developments to various types of engineering structures. Extensive …

This paper proposes a novel approach of time series analysis to identify the potential
changes in structural conditions, eg, degradation owing to accumulated damage. Although …