Anomaly detection in the concrete arc girder subjected to fatigue test

Abstract

A steel reinforced concrete arch of a bridge girder has been subjected to static and fatigue tests. The aim of this study is the application of guided waves in non-destructive diagnostics of civil engineering structures and early damage detection. Two piezoelectric transducers were mounted at a distance of 1 m to monitor area of the arch keystone. After every 500 000 cycles the signals of elastic waves have been measured and the girder visual examination was carried out. It turned out that both the load magnitude and the appearance of cracks have affected the signal changes. The obtained signal database has been used to train artificial neural networks and establish a diagnostic system. The results of the conducted tests have showed good sensitivity of anomaly detection and satisfying accuracy of load identification.