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 …

This manuscript provides a detailed synopsis of the contemporary advancements in the
nascent area of real-time structural damage detection for vibrating systems. The paper …

A data-driven reduced basis (RB) method for parametrized time-dependent problems is
proposed. This method requires the offline preparation of a database comprising the time …

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

The analysis presented in this work relates to the quantification of the effect of a selected set
of measured Environmental and Operational Parameters (EOPs) on the dynamic properties …

Dealing with the problem of large volumes of high-dimensional features and detecting
damage under ambient vibration are critical to structural health monitoring. To address these …

Data-driven damage localization is an important step of vibration-based structural health
monitoring. Statistical pattern recognition based on the prominent steps of feature extraction …

Structural health monitoring (SHM) has been increasingly exploited in recent years as a
valuable tool for assessing performance throughout the life cycle of structural systems, as …

Considering that traditional statistical regression and machine learning rutting prediction
models hardly capture time series characteristics of rutting, this study employed deep …

We propose a data-driven model to predict the short-term fatigue Damage Equivalent Loads
(DEL) on a wake-affected wind turbine based on wind field inflow sensors and/or loads …