QUICK‐B‐WIM: Large scale application of a moving force identification method on a railway bridge

Abstract

Globally, infrastructure faces the challenge of aging bridges and increasing traffic loads. Extended operational availability and safety of the bridge structures can be enabled by Structural Health Monitoring (SHM) methods. For this, knowledge of the actual vehicle loads is of crucial importance for evaluation of the remaining service life. Direct measurement of the moving loads, however, is either very cumbersome and requires considerable financial effort or in some cases even impossible. Bridge Weigh‐In‐Motion (B‐WIM) methods use the structural responses of bridge structures to determine the external vehicle loads. The present contribution deals with the testing of a novel moving force identification (MFI) method, denoted as Quick‐BWIM (QBWIM) under real operating conditions. In this study, 43 train crossings within 18 hours were investigated and compared with a nearby axle load measurement point. QBWIM achieves an average error of only 1.1% with a standard deviation of 7.5% for individual axles and an average error of 2.1% with a standard deviation of 1.5% for the identification of gross vehicle weights (GVW). This study shows that QBWIM can meet European and US guidelines even under poor conditions and is able to reliably determine axle loads in real time.