The heterogeneity of concrete is a major challenge for acoustic emission monitoring. A method of active-passive joint acoustic emission monitoring considering the heterogeneity of concrete is presented herein, and the time-frequency-space multi-parameter response characteristics of active and passive acoustic emission signals were studied in relation to the damage evolution of concrete. This method provides an idea of evaluating the damage state of concrete more actively and quantitatively than traditional methods. The results show that the microscopic damage model of concrete based on the acoustic emission penetrating wave velocity and amplitude is in agreement with the damage process of concrete. The standard deviation of the wave velocity up to 1000 m/s and the change rate of the amplitude up to −0.66 can be adopted as two signs that the load of concrete reached 70% of the ultimate load. The time-of-arrival localization based on variable velocity was used to correct the acoustic emission localization results, and the localization accuracy was increased by 44.74%. The damage process of concrete undergoes diverse changes; that is, the distribution of damage changes from heterogeneous to homogeneous and then back to heterogeneous. Hence, it is necessary for researchers to consider the heterogeneity of concrete when using acoustic emission monitoring. The active-passive joint acoustic emission monitoring is an effective method.

This study aims to elucidate the deterministic correlation between the microscopic fracture mechanisms and the multi-domain characteristics of acoustic emission in reinforced concrete beams under cyclic loading. Cyclic incremental tests were designed and conducted, with synchronized application of digital image correlation and AE techniques to capture the entire damage evolution process and corresponding signal responses throughout. The findings reveal that the damage stage division based on mechanical responses is consistent with that based on AE responses. Damage accumulation and irreversible processes can be clearly characterized by AE activity, and the systematic decrease in the Felicity ratio quantitatively verifies the irreversible accumulation of damage. Under cyclic loading, different microscopic fracture mechanisms generate AE frequency-domain signatures with statistically significant differences. A damage identification model integrating the Felicity ratio and multi-band energy features was developed, achieving an accuracy of 88.89% in identifying macroscopic damage stages. This research quantitatively confirms the effectiveness of AE characteristics as reliable identifiers of microscopic fracture mechanisms, providing a new basis for advancing structural health monitoring technologies grounded in fracture mechanism recognition.