An Investigation into the Diagnosis of Interturn Winding Faults in a Scaled-down DFIG using the MCSA and DWT of the Stator and Rotor Current

Abstract

In this work, an experimental test rig has been set up to enable the physical implementation of the stator and rotor interturn winding faults on a 5kW wound rotor induction machine (WRIM) that was developed and built in the university laboratory as a scaled-down version of a typical 2.5MW DFIG. To evaluate the performance of the developed test rig, experiments have been carried out by separately implementing the stator interturn short circuit faults (ITSCFs), rotor ITSCFs and a static eccentricity fault on the micromachine and capturing the real-time startup stator and rotor current signals for further analysis in MATLAB to diagnose the presence of these faults during both transient and steady state operating conditions. For fault diagnosis, two analysis techniques have been explored in this work: the conventional motor current signature analysis (MCSA) and the Discrete Wavelet Transform (DWT) analysis. To improve the fault diagnosis process, the Hilbert Transform (HT) technique has been applied on the captured transient stator and rotor current signals to remove the fundamental component that masks the fault-related components due to its higher magnitude. Therefore, the DWT analysis has been applied on the resultant Hilbert modulus of the stator and rotor currents to diagnose the faults under study. Moreover, spectrogram plots of the resultant signals have been used to indicate the evolution of the fault-related frequency components in the resultant Hilbert modulus of the stator and rotor current. The results have demonstrated that the analysis of the rotor current using either the MCSA, DWT or spectrogram technique provides a clearer indication of the presence of the stator ITSCF, rotor ITSCF and static eccentricity fault condition as compared to the analysis of the stator current signal. Therefore, it is concluded that the rotor current is best suited for diagnosing the different faults implemented on the micromachine.