## 6 Discussion and Conclusions  
Having ascertained the effectiveness of the three-leg approach through studying simple insulation test objects such as XLPE specimen, as seen by the test cell as in Figure 1, real electrical assets such as MV cables with artificially developed defects can be designed and investigated. In the first part of the paper, controlled surface discharges were generated on a simple XLPE flat specimen with a test electrode configuration that promotes surface PD. AC PD measurements were performed to determine the PDIV as well as the type of generated PD. The obtained results confirmed the occurrence of surface PD with 100% probability, and the determined AC PDIV value was used to validate the modelled PDIV\({}_{\text{AC}}\) that was calculated with the help of a generalized PD-inception model (Equation (1)) and simulated electric field profile.  
Reproducing artificial defects in insulation systems to investigate the phenomenology, time trend, and damage rate of PD is a diffused practice in university and industrial labs. However, it is also a common experience that defects not engineered properly either do not activate PD or do it at voltage levels that are not of interest for the testing purpose. Also, they might not incept the type of PD that is wanted.  
The above-mentioned three-leg approach, which is based on a modelled PD-inception field and calculates electric field distribution and validation through measurement analytics that can identify the type of source generating PD, was also proven to be successful in the case of real electrical insulation systems such as cable with artificially developed defects. The analytics software screenshots displayed by Figures 9 and 10 provide clear and unambiguous identification of PD sources as surface and internal, respectively, in case of AC, thus validating defect design and manufacturing technology. Also, Figure 11 highlights the operation of the automatic PD analytics software, which is able to identify the presence of different types of PD (surface and internal) at the same time, while Figure 12 indicates that defects can also be properly designed and manufactured for DC PD phenomena.  
The possibility of having available analytics and acquisition software that are fully automatic conforms to the proper and ineludible direction, that is, to make PD measurements not only simple but, particularly, to promote PD diagnostic and condition inference as an open asset for condition and maintenance operators that does not need experts or suffer the related delay times. In such a way, PD monitoring can become a part of an inte  
Figure 12: Typical screenshot from DC PD analytics software that illustrates how SRI works for surface defect at PDIV\({}_{\text{DC}}\); (**a**) global TRPD pattern, (**b**) PD pulse (**c**) separation (PCA) map, and (**d**) recognition of presence of PD by highlighting the option “Noise plus possibility of PD”.  
grated condition monitoring global process that can interact with central control systems of electrical assets (as SCADA) in a smart and effective way [26].  
Conceptualization, G.C.M.; methodology, G.C.M. and S.B.M.; software, S.B.M.; validation, S.B.M. and M.S.; formal analysis, G.C.M. and S.B.M.; investigation, G.C.M., S.B.M. and M.S.; resources, G.C.M.; data curation, S.B.M.; writing--original draft preparation, G.C.M.; writing--review and editing, G.C.M. and S.B.M.; visualization, S.B.M. and M.S.; supervision, G.C.M.; project administration, G.C.M. and M.S.; funding acquisition, G.C.M. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Office of Naval Research under grant number N00014-21-1-2124.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.