B0752
Title: Covariate-adjusted sensor outputs for structural health monitoring: A functional data approach
Authors: Philipp Wittenberg - Helmut Schmidt University (Germany) [presenting]
Abstract: Structural health monitoring (SHM) is increasingly applied in civil engineering. One of its primary purposes is detecting and assessing changes in structure conditions to reduce potential maintenance downtime. Recent advancements, especially in sensor technology, facilitate data measurements, collection, and process automation, leading to large data streams. A function-on-function regression approach is proposed for modelling the sensor data and adjusting for confounder-induced variation.
