## 4 Results and Discussion
### Parameter Correction Results  
AE activities of the specimens were localized using a new approach-based source localization algorithm that considers the medium's heterogeneity [25]. Then, localized activities were corrected using relevant input vs. output amplitude relations for their locations. Relations of recorded vs. corrected amplitudes of all specimens were examined using Figure 9. Second-order polynomial curves and equations calculated by regression  
Figure 8: Origination time of clustered AE activities (\(\bullet\) Cluster-1, \(\bullet\) Cluster-2).  
analysis indicating the most appropriate behavior for these distributions are also presented on the graphs. It is seen that, the corrected amplitudes of the hits around 40 dB (threshold) vary over a wide range. However, this interval narrows as the recorded amplitude increases. This indicates that hits having different amplitudes recorded by the same sensor can be perceived as having equal amplitude due to different attenuation factors. Moreover, as the amplitude of the activity increases, the need for correction decreases. As the recorded amplitude value increased, the proximity to the corrected values increased and the closeness to the actual amplitude value reached up to 90% for the highest amplitudes. In addition, when the closeness of the recorded amplitude values to the corrected values is evaluated, it is observed that the presence of the steel fiber decreases the level of closeness, while the presence of polypropylene and polyamide fibers increases. Actual amplitude values recorded in cement mortar are also closer to recorded ones compared to the reference specimen, which is more attenuative due to the presence of coarse aggregates.  
To evaluate the signal amplitude variation according to the concrete content (fiber types and amounts), closeness values between recorded and corrected amplitude were  
Figure 9: Recorded vs. corrected amplitude relations.  
Figure 11: Raw RA value distributions of the AE activities (* Raw RA value, * ** Moving average of raw RA value, — Load).  
Figure 12: Corrected RA value distributions of the AE activities (\(\bullet\) Corrected RA value, \({}^{**}\)\({}^{**}\) Moving average of corrected RA value, — Load).  
Figure 14 shows energy loss versus amplitude loss of the AE activities. As can be seen, AE signals lost their amplitudes at a maximum of 70-80% and at least 60% of their  
Figure 13: Average frequency distributions of the AE activities (\(\bullet\) Average frequency, \({}^{***}\) Moving average of average frequency, — Load).  
energy. This shows that the energy of an AE signal is distorted more than the amplitude by attenuation. The reason for this situation is that as the wave attenuates, counts exceeding the threshold and the signal's duration decrease, and the energy decreases accordingly. Considering the amplitude loss of the activities that lost all their energy and were listed at nearly 100% energy loss, the following evaluation can be made: among the activities that lost energy at the same rate, the activities with lower amplitude loss lost more AE duration. Activities with higher amplitude loss, on the other hand, and the same amount of energy loss, loss in AE duration was less. Accordingly, it can be concluded that under the same energy loss, activities with less amplitude loss are characterized by more tensile type, and activities with more amplitude loss are characterized by more shear type. Considering all of these evaluations, a new inference for a relationship between the amplitude and energy losses and the type of damage was proposed as in Figure 15.  
Figure 14: Amplitude and energy losses of the AE activities.