Automated seismic event detection considering faulty data interference using deep learning and Bayesian fusion

Abstract: Structural health monitoring (SHM) aims to assess civil infrastructures’ performance and ensure safety. Automated detection of in situ events of interest, such as earthquakes, from extensive continuous monitoring data, is important to ensure the timeliness of subsequent data analysis. To overcome the poor timeliness of manual identification and the inconsistency of sensors, this paper proposes an automated seismic event detection procedure with interpretability and robustness. The sens