Travelling Wave Field Data Contingency Screening Based on Semi-supervised Clustering Using Generalized Current Modal Component

Transient high-speed data acquisition of traveling wave is usually set low triggering thresholds.This can ensure it be started in the case of high impedance fault,while some disturbance signals not caused by the fault are also recorded and this make the recorded data seriously imbalanced.It is difficult to effectively screen the contingency data from the imbalanced multi-channel data.Fractal dimension and transient energy of general modal current component for multi-transmission lines on the same bus was selected as characteristic vectors in this paper.With the help of some knowledge,such as the continuity of the historical events records and the following events,the compact support in time domain and so on,the constrained semi-supervised clustering was formed through the "anchor" composed by a small amount of labeled sample set and neighborhood constraints of unlabeled sample set in time domain.And data-driven classification method for traveling wave field data based on domain knowledge was proposed,which makes the screening feasible and effective for massive multi-channel waveform records.The proposed method proved feasible and effective.