Developing a new acoustic emission source classification criterion for concrete structures based on signal parameters

Abstract

Acoustic emission (AE) signal parameters can be used to classify the source type in concrete structures. However, signal parameters are influenced by the wave propagation from the source to the receiver, leading to wrong source classification results, especially for monitoring large concrete structures. This paper experimentally evaluates the influence of wave travel distance on signal parameters on a full-scale shear test of a reinforced concrete beam. The evaluated signal parameters include the RA value, average frequency, peak frequency, frequency centroid, and partial power. The evaluation reveals the limitation of using RA value - average frequency trends in large scale structural concrete members. Based on the evaluation, we propose a new source classification criterion using peak frequency or partial power, which can effectively classify the source type. The new criterion is also validated in a reinforced concrete slab test, which is another structural type. Based on the new criterion, we suggest a sensor layout that is suitable for source classification for large concrete structures. The results of this paper can help developing a reliable solution for real-time source classification for large concrete structures in general.