Transformer Winding Deformation Fault Diagnose Based on FRA and Energy Feature Extraction by Wavelet Packet

Abstract

When different types and extent of faults occurs at transformer winding, the energy of the signals in different frequency bands will change. So it can calculate the characteristic energy of different response signals at different states to determine whether the winding failure. The transformer fault diagnosis method based on FRA and characteristic energy extraction is presented, the maximum cross-correlation between the signal and the wavelet was taken as criterion to choose the wavelet. The method is verified by test. Experimental results show that this method can diagnose winding fault type and extent effectively, and improve the sensitivity of fault diagnosis.