Damage identification of brick masonry under cyclic loading based on acoustic emissions
Ageing infrastructure, such as masonry railway bridges, suffers from structural deterioration due to fatigue loading. This paper presents an experimental study of brick masonry deterioration under gradually increasing cyclic loading with the aid of Acoustic Emission (AE) sensors. Two masonry beams were tested in the laboratory under similar stress conditions that masonry arches experience during train loading. An in-house AE monitoring system was developed for this study allowing both feature-based and waveform-based AE analysis. In the lab tests, different modes of damage were activated, such as tensile bond failure, brick and mortar crushing, diagonal shear failure and joint sliding. Feature-based AE analysis shows an increase in cracking rate before brittle failure events that is not necessarily accompanied by an increase in deformation rate. Statistical analysis reveals clear trends in AE results that correlate to different damage stages. The paper discusses how these findings can be leveraged to develop real-time structural alert systems that could provide early warning of damage before a significant increase in dynamic deformation occurs.
Technology Strategy Board (920035)