## 4 Experimental Validation
### PDIV Measurements and Discussion  
Repeated PDIV\({}_{\text{AC}}\) measurements were performed on XLPE specimens using electrodes A (Figure 5) and B (Figure 6). The purpose was to validate the PDIV estimations summarized in Table 3.  
The PDIV\({}_{\text{AC}}\) measurement procedure was the same for both electrodes. The AC voltage at the HV electrode was slowly increased by steps lasting 30 s to record and analyze PD at each voltage step by means of the SRI software. The procedure was continued till the PDIV\({}_{\text{AC}}\) value was reached, which is the voltage level at which the PD activity starts persistently [20]. Five measurements were conducted for the same test arrangement after de-energizing the sample and waiting for enough time (approximately 5 min) to make sure that PD-generated space charge was not able to affect successive PD measurements. Table 4 reports the PDIV\({}_{\text{AC}}\) measurement values for each acquisition with electrodes A and B. Besides the PDIV\({}_{\text{AC}}\) values obtained from each measurement, the mean values within the 95% confidence intervals, considering a Gaussian distribution for the measurement data, are reported [21]. For electrode A, PDIV\({}_{\text{AC}}\) is 1.2 \(\pm\) 0.3 kV (PD identified as internal), whereas for electrode B, it is 1.7 \(\pm\) 0.3 kV (PD identified as surface). It is noteworthy that PD are identified as internal with a likelihood of 0.9 to 1 for electrode A, and surface with a likelihood of 0.8 to 1 for electrode B. The likelihood level is a number between 0 and 1, and it comes as an output of the fuzzy engine used for automatic identification [18]. For example, a likelihood 1 of surface PD means that the collected PD signals certainly come from surface discharges, whereas a likelihood 0.5 internal and 0.5 surface means that most likely both gas and surface sources contribute to generating the detected PD signals. This result is consistent with the observation made in Section 3 (see Table 3), referring to the simulations and the inception models. The PDIV values of Table 3 to be considered are 1.2 \(\pm\) 0.3 kV for electrode A, for which gas PD are triggered for a voltage threshold lower than the one for surface discharges, and 1.7 \(\pm\) 0.3 kV for electrode B, for which surface PD are triggered for a voltage threshold lower than that for gas discharges. Indeed, comparing the measured PDIV of Table 4 with those in Table 3, a good fit between the experimental results and the predicted values is observed since the estimated PDIV values are placed inside the uncertainty interval of the measured quantities. Therefore, the three \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Electrode A**} & \multicolumn{2}{c}{**Electrode B**} \\ \hline
**N. of** & & & & \\
**Acquisition** & **PDIV (kV)** & **ID** & **PDIV (kV)** & **ID** \\ \hline
1 & 1.3 & Internal 1 & 1.6 & Surface 1 \\
2 & 1.1 & Internal 1 & 1.7 & Surface 1 \\
3 & 1.2 & Internal 1 & 1.6 & Surface 0.8 \\
4 & 1.1 & Internal 1 & 1.8 & Surface 0.9 \\
5 & 1.3 & Internal 0.9 & 1.8 & Surface 1 \\ \hline  & \multicolumn{2}{c}{PDIV\({}_{\text{AC}}\) = (1.2 \(\pm\) 0.3) kV} & \multicolumn{2}{c}{PDIV\({}_{\text{AC}}\) = (1.7 \(\pm\) 0.3) kV} \\  & Predominantly internal & \multicolumn{2}{c}{Predominantly surface} \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Repeated PDIV measurements performed by electrodes A and B: each measurement is associated with its PD identification likelihood (ID) obtained by the SRI software. The final results are given in terms of the mean PDIV within its 95% confidence intervals. leg approach is validated in the experiments involving both electrodes. Notably, correct surface discharge testing is achieved only by electrode B, since A triggers more likely gas discharges (identified as internal) than surface discharges. Figures 11 and 12 show two examples of graphical outcomes produced by the SRI software by using electrode A (Figure 12) and electrode B (Figure 12).