Single-phase-to-ground Fault Diagnosis Based on Waveform Feature Extraction and Matrix Analysis

A large proportion of the distribution network operates under neutral point ungrounded mode or arc suppression coil grounded mode. The single-phase-to-ground fault current is small, which brings difficulties to fault diagnosis. A single-phase-to-ground fault section identification method is proposed based on synchronous waveform feature extraction and matrix analysis. Firstly, the proper features are extracted from the current waveforms of grounding phase obtained with fault recorders, which are used to construct topology matrix. Then, random matrix theory is used to get the random matrix eigenvalues. Using the distribution of the eigenvalues, K-means clustering algorithm is utilized in clustering the fault cases and get the final classification center point. Through finding the central point which has the smallest distance with new faulty data set, the fault section can be automatically identified. The effectiveness of proposed method is verified by IEEE 34 nodes test system.