In recent years role of wound-field synchronous machines increases very prominently in the area of EV’s. So the motors are operated at dynamic conditions and leads various failures. In this regard this paper presents the stator winding related inter-turn short circuit faults detection and phase identification in electrically excited wound-field synchronous machines. Practically in most of the cases the captured current signals are contaminated with noise. In this paper, suggest a wavelet multi resolution analysis along with adaptive threshold based algorithm to detect and identify the faulty phases of a 3-ɸ wound-field synchronous motor operated over a wide range of operating power factors like unity, lagging and leading. In order to find the 3-ɸ currents fault residues a stationary wavelet transform is employed and extract the disturbance information from the 3- ɸ residue currents by using discrete wavelet transform. To find the fault location and phase identification a 3-ɸ energies and Fault index are compared with adaptive thresholds. Finally, the algorithm is tested with practical data for various levels of inter-turn short circuit faults. The successfulness and validity of a proposed algorithm is clearly demonstrated from acquired results.
Volume 12 | Issue 2
Pages: 2155-2165
DOI: 10.5373/JARDCS/V12I2/S20201261