abstract
- © 2019 Elsevier Ltd Turn-to-turn short circuits occur due to insulation damage in transformer windings and these may potentially result in catastrophic faults affecting electric networks. In fact, transformer diagnosis plays an important role for preventing large energy outages. A new sensitive method based on wavelet transform for identifying interturn faults during energization of single-distribution transformers is presented. The diagnosis is performed utilizing the magnetizing currents obtained during transformer energization under healthy and faulty conditions. Magnetization currents are processed with the wavelet transform and using correlation matrices, which in turn are used to obtain a time-frequency power spectral density (PSD); these are used to quantify the damage level when transformer windings are experiencing faults during their energization. The proposed method was analyzed during simulations using ATP-EMPT software and experimental tests were also carried out in laboratory to validate the results.