39 citations · 75 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
Benchmarking Sensor-Fault Robustness in Forecasting
Alexander Windmann, Philipp Wittenberg, Gianluca Manca +3
Cyber-physical system (CPS) forecasting models depend on sensor streams with noisy, biased, missing, or temporally misaligned readings, yet standard forecasting evaluation often se…
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…
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…