Recognition of Partial Discharge in Medium Voltage Switchgear via Gray-Scale Diagram and Support Vector Machine

Partial discharge (PD) has been proved to be a sensitive indicator to reveal the insulation condition of medium voltage (MV) switchgear. Since the influence of a PD on MV switchgear strongly depends on its type and location, accurate recognition of the PD is crucial to improve the efficiency of on-site measurement and optimize the maintenance strategy. Accordingly, this paper develops a PD recognition method based on gray-scale diagram and support vector machine. Labeled signals including many PD pulses are transformed into a gray-scale diagram via a two-dimensional maximum margin criterion, significantly reducing the dimensionality of the PD data thus improving computing efficiency. Models of different types of PD defects are then trained by applying the support vector machine to the labeled gray-scale diagrams. Eventually, the type of a PD is identified via the trained models. The effectiveness and feasibility of the proposed method are verified on four artificial PD models and three simulated PD defects on a real 10-kV switchgear.