Structural health assessment through continuous vibration-based monitoring of a stainless-steel lattened in-operation railway bridge

Abstract

Damage detection in railway bridges is challenging due to changing environmental and operational conditions. Advanced monitoring techniques, such as operational modal analysis (OMA), use vibration to assess the integrity of structures during their operational life. Cov-SSI, a time-based OMA algorithm, is widely used for the automatic identification of system dynamics. Static modelling is essential to separate variability from benign effects and ensure accurate monitoring. Monitoring the health of the structure through control charts highlights damages that influence the dynamic response. This study focuses on the continuous monitoring of railway bridge networks using advanced methods such as MOVA and MOSS. In particular, this work is part of a research project dedicated to the continuous monitoring of a real bridge in operation: the Quisi Viaduct in Alicante (Spain). The viaduct is a stainless steel single-span bolted railway bridge, built at the beginning of the 20th century. The viaduct is equipped with a set of high-sensitivity accelerometers and a dense network of deformation sensors that store a compendium of data of approximately 3 years. This contribution discusses the quality of the data sets and the monitoring strategy, with a focus on the effectiveness of using statistical process control charts to assess the structural health of railway bridges.