# Validation of Acoustic Emission Waveform Entropy as a Damage Identification Feature
## 5 Validation and Discussion
### Correlation Between the Coupon Specim and Real Structures under Operation
Like the AE entropy, it can be observed in Figure 18c-e that during  
Figure 20: Fatigue loading for the coupon specimen. the initial yielding, there was also a noticeable increase in the traditional AE features (e.g., count, energy and peak amplitude). The yielding/deformation activities in the primary wall of the cargo tank, due to single sloshing impact are an important source of information as they are considered to be a dominant damage mechanism during voyages [54; 55]. Since AE entropy is capable of providing a noticeable indication during yielding, it can be successfully applied to monitor the primary wall against this damage mechanism. The information of yielding/deformation in the primary wall can educate the ship operators regarding the structural condition of the cargo tank so that appropriate maintenance can be planned to avoid further failure and shut down costs. It can be observed from Figure 16c-f that the yielding in tensile test was not accompanied by a noticeable increase in AE entropy and the traditional features (e.g., count, energy and peak amplitude), unlike in the fatigue test. This difference in AE behaviour between the tensile and fatigue specimen arises due to their respective loading conditions. The tensile specimen was subjected to a constant strain rate of 0.0040 or 1 mm/s from start of the test until fracture whereas the fatigue specimen was subjected to a strain rate of 0.157 during the initial yielding (due to the onset of loading). In comparison to the loading at a constant strain rate during tensile test, the strain rate at the onset of yielding in fatigue test was significantly higher. Strain rate has been shown to enhance the AE events generation in a wide range of materials such as \(\alpha\) brass [56], 7075-T6 aluminium [57], discontinuous yielding material [58], single crystal copper [59] and austenitic stainless steel [20; 22]. For instance, in \(\alpha\) brass, the count of AE events increases with the strain rate [56]. In 7075-T6 aluminium [57], the root mean square (RMS) voltage of AE events was proportional to the strain rate. The increase in strain rate on single crystal copper was accompanied by an increase in count and RMS voltage of AE events [59]. In austenitic stainless steel [20; 22], with the increase in strain rate, the RMS voltage, count and frequency content of the AE events has been shown to increase. The increase in AE event generation, in all these studies, was attributed to the increase in rate of source activation instead of the formation of the new source. In austenitic stainless steel, this increased rate of source activation refers to the increase in velocity of the mobile dislocation [22]. In other words, with the strain rate, the velocity of the mobile dislocation also increases. It has been reported in references [20; 60] that the strain rate in austenitic stainless steel is related to the mobile dislocation velocity according to Equation (3):  
\[e=p_{m}bv_{av} \tag{3}\]  
where \(e\) is strain rate, \(p_{m}\) is the dislocation density, \(b\) is the Burgers vector and \(v_{av}\) is the average dislocation velocity. It has also been reported in reference [61] that the squared RMS voltage of the AE waveform recorded during deformation is directly proportional to the strain rate in many single and poly crystals. The relation between the strain rate and RMS voltage, according to this study is shown in Equation (4), where \(e\) is the strain rate, _Vrms_ is the RMS voltage and t is the window length of the waveform. \[\text{t}\times\text{V}_{RMS}^{2}\propto e \tag{4}\]  
Thus, from Equations (3) and (4), it can also be deduced that the voltage RMS is related to the dislocation density \(p_{m}\), the Burgers vector \(b\) and the average dislocation velocity \(v_{av}\). The equation relating these quantities is shown in Equation (5).