This study presents a novel artificial neural network (ANN) based methodology within a
vibration-based structural health monitoring framework for robust damage detection. The …

This study presents a stationarity-based method, based on sliding window principle, for wind
turbine monitoring and anomaly detection. Initially, the window is formed with a reference …

The paper presents a case study demonstrating the methods used to estimate the value of
the information (VoI) delivered by a structural health monitoring (SHM) system. The …

A significant problem associated with the implementation of Vibration-Based Structural
Health Monitoring (VSHM) systems originates from the detrimental effects caused by …

A significant issue that has plagued data-driven Vibration-based Structural Health
Monitoring (VSHM) is the mitigation of Environmental and Operational Variations (EOVs) …

Cointegration theory has been recently proposed for condition monitoring and fault detection
of wind turbines. However, the existing cointegration-based methods and results presented …

Data-driven models have become powerful tools for structural and condition monitoring of
engineering systems, particularly wind turbines. This paper presents a comparative analysis …

Although Lamb waves have found extensive use in structural damage detection, their
practical applications remain limited. This limitation primarily arises from the intricate nature …

In this paper a novel Data-Driven Design and Operation approach is introduced for an
offshore wind energy application to account for site-specific conditions. Data from …

In an era marked by rapid urbanization and increasing environmental concerns, the quest
for sustainable development has become paramount. The goal of this study is to support …