Bayesian anomaly detection for a steel plate girder bridge using optimized sensor arrangement by means of the EFI method

Abstract

This study aims to investigate the effectiveness of a Bayesian hypothesis-based Bayesian damage detection using sensors arrangement optimized by means of the effective independence (EFI) method. The feasibility of Bayesian anomaly detection is verified using vibration and damage experimental data on an actual steel plate girder bridge. The optimal sensor arrangement and Bayesian anomaly detection for the bridge are also investigated using finite element analysis. Observations demonstrated that it is possible to detect damage and to identify the damage location approximately even with optimally arranged three sensors. In addition, the EFI method was also useful in Bayesian anomaly detection.