Yuxuan Zhang

Multi-type data anomaly detection for structural health monitoring using interpretable machine learning methodology

Structural health monitoring (SHM) systems utilize multi-type monitoring data, particularly data collected under extreme events, to assess safety and serviceability during structures’ lifetime. However, sensor faults can compromise the reliability of structural analysis. This study proposes a novel interpretable data a...