# Acoustic Emission for Structural Monitoring of Historical Masonry: An In-Field Application
## 1 Introduction  
Acoustic Emission (AE) is a non-invasive, non-destructive technique particularly suited for Structural Health Monitoring across a wide range of applications, including infrastructure, reinforced concrete elements, and historic masonry buildings. While AE has been extensively applied to concrete structures [1], its use in masonry remains more complex due to the intrinsic heterogeneity of the materials and the considerable attenuation of signals. In masonry, AE wave propagation is influenced by various factors, such as the density and stratigraphy of the construction, the presence of voids, and the nature of the mortar joints. Generally, wave velocities are higher in bricks and masonry blocks than in mortar. Interfaces between different components--such as brick-to-mortar contacts, pre-existing cracks, and composite wall sections--can act as reflective barriers, further complicating signal transmission [2]. These characteristics render the interpretation and localisation of AE signals in historic masonry particularly challenging. The AE signal is typically composed of high-frequencyelastic waves ranging between 5 kHz and 5 MHz, well outside the audible range [3]. The source-to-sensor path, along with the presence of internal inhomogeneities, plays a fundamental role in shaping signal features, making source identification in masonry far from straightforward [2]. Nevertheless, AE remains an effective diagnostic method for evaluating damage evolution in historic masonry, especially under conditions of long-term load, fatigue, or seismic action [4; 5; 6]. AE enables real-time detection of micro- and macro-crack initiation, offering valuable insight into damage progression without compromising the structural integrity of the artefact [7]. Among the most widely adopted approaches is the parametric analysis of AE signals, which relies on basic parameters such as signal amplitude, counts, energy, and Rise Time [8]. More advanced techniques, such as the Load-Calm method, have been successfully applied to masonry to track AE activity over successive loading cycles [9]. This approach is particularly useful as it focuses on relative activity levels, rather than absolute signal amplitude, thus mitigating the effects of attenuation typical in masonry [8]. Additionally, the application of classical AE concepts such as the Kaiser effect and the Felicity ratio has proven valuable in masonry diagnostics [10; 11]. The Kaiser effect refers to the absence of AE activity below previously reached load levels, while the Felicity ratio quantifies deviations from this ideal behaviour, offering insight into internal damage accumulation [10]. These effects are less sensitive to signal degradation, making them well suited for applications in irregular, historic walls [8]. Significant research efforts have also been directed towards linking AE signal features with damage mechanisms through analytical or numerical models. For instance, [PERSON] et al. proposed a correlation between AE data and fracture mechanics theory [12], while multiscale approaches have linked AE activity to the fractal dimension of crack patterns [13; 14]. Other studies have employed finite element modelling and lattice models to simulate AE behaviour in masonry under mechanical loads, providing a basis for interpreting real-time monitoring results [6; 15]. An illustrative in situ application was reported by [PERSON] et al., who performed a load test on a historic vaulted masonry structure using water cushions as distributed loads. AE monitoring revealed activity only after surpassing the previously reached load level, providing experimental evidence of the Kaiser effect in historic masonry [16]. Despite certain limitations--such as the lack of a direct quantitative correlation between AE parameters and damage severity and sensitivity to environmental noise--AE remains a highly valuable technique for heritage conservation [17]. Its advantages include real-time monitoring, the ability to detect early-stage damage, and minimal invasiveness.