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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…
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…
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…
Confounder-adjusted Covariances of System Outputs and Applications to Structural Health Monitoring
Lizzie Neumann, Philipp Wittenberg, Alexander Mendler +1
Automated damage detection is an integral component of each structural health monitoring (SHM) system. Typically, measurements from various sensors are collected and reduced to dam…
Covariate-Adjusted Functional Data Analysis for Structural Health Monitoring
Philipp Wittenberg, Lizzie Neumann, Alexander Mendler +1
Structural Health Monitoring (SHM) is increasingly applied in civil engineering. One of its primary purposes is detecting and assessing changes in structure conditions to increase…