7 papers
Higher-Order Multivariate Environmental Influences in Structural Health Monitoring
Lizzie Neumann, Philipp Wittenberg, Jan Gertheiss
System outputs such as eigenfrequencies or strain data, often used in structural health monitoring (SHM), not only react to damage but also depend on environmental conditions. When…
Removal of Multivariate Environmental Influences in Structural Health Monitoring through Conditional Covariances and Supervised Learning
Lizzie Neumann, Philipp Wittenberg, Jan Gertheiss
In structural health monitoring (SHM) systems, data is collected from a multitude of sensors measuring, for example, vibration or strain in the structure, along with additional fea…
Feature Reconstruction and Monitoring of Load Test Data under Varying Environmental Conditions
Lizzie Neumann, Philipp Wittenberg, Alexander Mendler +1
System outputs in Structural Health Monitoring (SHM), such as sensor measurements or extracted features like eigenfrequencies, are influenced not only by (potential) damage but als…
Covariate-Dependent Functional Principal Component Analysis for SHM
Philipp Wittenberg, Lizzie Neumann, Kristof Maes +1
In Structural Health Monitoring (SHM), sensor measurements and derived features such as eigenfrequencies often exhibit systematic daily patterns and can therefore be naturally repr…
Confidence Intervals for Conditional Covariances of Natural Frequencies
Lizzie Neumann, Philipp Wittenberg, Jan Gertheiss
In structural health monitoring (SHM), sensor measurements are collected, and damage-sensitive features such as natural frequencies are extracted for damage detection. However, the…
Multivariate Long-term Profile Monitoring with Application to the KW51 Railway Bridge
Philipp Wittenberg, Alexander Mendler, Sven Knoth +1
Structural Health Monitoring (SHM) plays a pivotal role in modern civil engineering, providing critical insights into the health and integrity of infrastructure systems. This work…