Abstract
Leakage current on contaminated polymer insulators was analyzed using digital signal processing techniques. Salt-fog tests with non-soluble deposit were conducted in a laboratory, during which leakage current was separated into conductive, dry-band arc and their transition components. The time-integrated value (cumulative charge) of each component was measured. A prototype of artificial neural network-based system that can estimate hydrophobic states and contamination levels at the surface of polymer insulators by employing leakage current information was constructed.
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