Data-Driven Damage Detection Based on Moving-Loads Responses - The Luiz I Bridge

Abstract

In the last decades, structural health monitoring (SHM), and, in particular, early damage detection methodologies, have emerged as an important tool to assist in the maintenance and management of infrastructures. In this context, this work presents a methodology for damage detection in full-scale bridges based on moving-loads responses. The Luiz I bridge, an outstanding centenary steel double-deck arch bridge, was selected as a case study. The methodology consists in building time-series of vehicle-influence lines of the strains observed in the selected cross-sections and processing data by using moving principal component analysis (MPCA). Firstly, the effectiveness of the approach is assessed on numerically-simulated data, to show, on the one hand, the stability of the approach under undamaged conditions, and, on the other, the ability of the approach to highlight changes in the structural condition. Finally, the methodology is applied on field data collected for a 3-months period.