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 …

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

Structural condition identification based on monitoring data is important for automatic civil
infrastructure asset management. Nevertheless, the monitoring data are almost always …

This is the third and final paper in a series laying foundations for a theory/methodology of
Population-Based Structural Health Monitoring (PBSHM). PBSHM involves utilising …

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 …

This paper is the second in a series of three which aims to provide a basis for Population-
Based Structural Health Monitoring (PBSHM); a new technology which will allow transfer of …

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 …

Deep Neural Networks (DNNs) trained on one dataset (source domain) do not perform well
on another set of data (target domain), which is different but has similar properties as the …

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

Modeling uncertainty or modeling error has been widely recognized as one major challenge
in structural model updating for structural identification and damage detection. It renders …