Shi-Qing Jia

Data anomaly detection for structural health monitoring based on Markov transition matrix features and XGBoost

Structural health monitoring (SHM) systems produce enormous amounts of data over time. However, abnormal data caused by sensor breakdowns and environmental interference greatly reduce the Accuracy of structural state evaluations. This study develops and evaluates a low-dimensional feature representation strategy for an...