PD INFERENCE FOR THE DETECTION OF ELECTRICAL TREEING IN INSULATION SYSTEMS

Partial discharge (PD) measurements constitute one of the most promising tools for electrical insulation diagnosis. This paper describes how a procedure based on PD measurements can provide early detection of electrical trees in polymeric insulation systems. Such an application relies upon a new methodology, which provides enhanced tools for the identification of PD generating defects. Tree inference is carried out step wise. Acquired signals are primarily separated according to their waveform, thus achieving data sets related to a specific PD typology. Then, fuzzy algorithms are applied to PD height and phase derived quantities belonging to these homogeneous datasets, in order to assign a membership degree to specific output categories. If the data set is relevant to an internal defect, a further analysis is performed in order to establish whether or not this defect is a treed region. The algorithm described in this paper was developed resorting to tests performed on artificial test