Determination of yielding point by means a probabilistic method on acoustic emission signals for application to health monitoring of reinforced concrete structures

Abstract

Reinforced concrete (RC) flanged beam specimens were tested under incremental cyclic load till failure in flexure, and simultaneously, the acoustic emission (AE) signals released by the specimens were recorded. To assess damage in RC structures, a previously published index of damage (ID) based on AE signals was used. This index, however, needs to know the yielding point of the specimen. In the present study, yielding point was identified with a probabilistic method known as Gaussian mixture modeling (GMM) applied to the AE signals, as compared with that obtained by means of the plastic strain energy. It was observed that yielding load obtained with both methodologies was almost same, thus validating the GMM method. This result permits to use the ID index for damage monitoring of RC structure in practical scenarios, by using only information hidden in the AE signals. The influence of loading rate, failure type (tensile and shear), RC beam depth, concrete compressive strength, and percentage of tensile steel reinforcement on ID were studied in this work.