# Acoustic Emission for Structural Monitoring of Historical Masonry: An In-Field Application
## 5 Results
### AE Results  
The load test had an overall duration of approximately 2 h and 20 min.  
Each loading/unloading step lasted sufficiently long to allow the signals to stabilise, with particular attention to AE.  
The following figure (Figure 8) presents the cumulative number of AE hits recorded by each sensor over time, in correlation with the applied load curve.  
The graph clearly illustrates the brief duration of the first cycle and the near-complete absence of AE activity during this phase. This outcome is primarily attributed to an overly high initial threshold setting, which hindered the detection of AE events with amplitudes below the threshold level.  
It is important to note that the test was inherently unrepeatable due to the progressive and irreversible nature of the damage mechanisms--such as micro- and macro-cracking--being investigated. Consequently, it was necessary to dynamically adapt the acquisition parameters in real time, particularly in response to fluctuations in background noise during the experiment. The revised threshold was validated using repeat Hsu-Nielsen pencil lead break tests, which confirmed the system's ability to detect real AE events within the site-specific noise environment. Signal validation was further supported by temporal and spatial correlation with mechanical loading steps and source localization patterns consistent with expected stress concentrations.  
During the second loading cycle, after adjusting the threshold value, moderate AE activity was observed. Notably, an event was detected by sensors 3 and 4 during the loading phase between 5.00 and 11.25 kN, followed by a subsequent event recorded by sensors 2 and 3 at the maximum load of 20.00 kN. AE activity of moderate intensity was also observed during the unloading phases.  
In the third cycle, between 0 and 10.00 kN of applied load, a significant AE event was detected by all sensors, with sensors 3 and 4 registering the highest intensity. Upon reaching the peak load of 20.00 kN and during a substantial portion of the unloading phase, multiple high-intensity events were recorded across all sensors, with a concentration of hits again noted in sensors 3 and 4. The AE activity gradually stabilised during the final unloading stage from 10.00 to 0 kN.  
To gain further insight into the origin of the AE signals, a linear source localisation analysis was conducted using the Arrival Time Method. This approach compares the first  
Figure 8: Cumulative hits over the duration of the loading test.  
hit times across the sensor network, whereby the Arrival Time is defined as the moment the signal exceeds the detection threshold.  
Figure 9 presents the results of the source localisation procedure.  
The graph highlights a concentration of phenomena between sensors 3 and 4, accompanied by the presence of lower-intensity sources near the keystone and in proximity to sensor 2. The subsequent image illustrates the area of the arch affected by the most intense sources, highlighted in green (Figure 10). In other words, while Figure 9 illustrates the localised AE sources using the Arrival Time Method, mapping each event along the sensor axis based on relative time differentials, Figure 10 adds to this representation with a simplified plan view of the arch, projecting the most intense AE activity zones onto the architectural layout. This view offers a clearer visual correlation between the identified AE sources and the physical structure, supporting the spatial interpretation of stress concentration areas within the arch.  
Figure 10: Plan view showing the positioning of the highest-intensity AE sources.  
Figure 9: Source localisation.