This study focuses on extracting information from partial discharge signals to identify aging processes in insulation systems. Utilizing high-frequency online measurements and artificial intelligence (AI) algorithms, the condition and type of phenomena affecting the insulation are determined. Twisted pair samples, prepared according to IEC 60851-5, were subjected to controlled thermal stress. Partial discharge signals were monitored and recorded at intervals during the aging process. The acquired data were analyzed using clustering algorithms, and the trends of number and amplitudes of the clusters were compared to trace the aging evolution.
AI Algorithms for Post-Processing and Analysis of Partial Discharge Signals During Ageing of Insulation
Della Giovanna, L.;Guastavino, F.;Khan, I.;Raza, M. H.;Torello, E.
2025-01-01
Abstract
This study focuses on extracting information from partial discharge signals to identify aging processes in insulation systems. Utilizing high-frequency online measurements and artificial intelligence (AI) algorithms, the condition and type of phenomena affecting the insulation are determined. Twisted pair samples, prepared according to IEC 60851-5, were subjected to controlled thermal stress. Partial discharge signals were monitored and recorded at intervals during the aging process. The acquired data were analyzed using clustering algorithms, and the trends of number and amplitudes of the clusters were compared to trace the aging evolution.
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