Partial discharges (PD) phenomenon for HVAC (High-Voltage-Alternating-Current) systems has already been widely studied in literature and from this it has been possible to produce a regulatory document that provides indications for description and identification of the different types of discharges. However, the growing diffusion of HVDC (High-Voltage-Direct-Current) systems makes necessary the development of analysis techniques also for DC case. In this paper data obtained from PD measurement under DC voltage were analyzed through the time-frequency map combined with a density-based clustering algorithm. The results show that, with this approach, it's possible to perform a noise rejection and recognize PD pulses of different sources.
Fatta A.D., Romano P., Imburgia A., Rizzo G., Vigni V.L., Albertini M., et al. (2022). Statistical analysis techniques for Partial Discharges measurement under DC voltage. In ICD 2022 - IEEE 2022 4th International Conference on Dielectrics (pp. 344-347) [10.1109/ICD53806.2022.9863226].
Statistical analysis techniques for Partial Discharges measurement under DC voltage
Romano P.;Imburgia A.;Rizzo G.;
2022-06-01
Abstract
Partial discharges (PD) phenomenon for HVAC (High-Voltage-Alternating-Current) systems has already been widely studied in literature and from this it has been possible to produce a regulatory document that provides indications for description and identification of the different types of discharges. However, the growing diffusion of HVDC (High-Voltage-Direct-Current) systems makes necessary the development of analysis techniques also for DC case. In this paper data obtained from PD measurement under DC voltage were analyzed through the time-frequency map combined with a density-based clustering algorithm. The results show that, with this approach, it's possible to perform a noise rejection and recognize PD pulses of different sources.File | Dimensione | Formato | |
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