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    Rotor Electrical Fault Detection in DFIGs Using Wide-Band Controller Signals
    (Ieee-Inst Electrical Electronics Engineers Inc, 2021) Sarma, Nur; Tuohy, Paul M.; Mohammed, Anees; Djurovic, Sinisa
    This paper presents a novel study of the wide-band spectral signatures in the controller signals of doubly fed induction generators (DFIGs) for the identification of rotor electrical faults. The aim is to advance the understanding of diagnostic information obtainable from the readily available DFIG controller signals. Analytical equations defining the controller signals possible spectral contents are derived to enable characterization of spectral signatures and their correlation to operating conditions and rotor faults. The equations are verified in a DFIG harmonic model study and also validated by undertaking a range of experiments on a laboratory DFIG test-rig. It is shown that the calculated, simulated and experimental results are in good agreement with regards to representing fault induced signatures in the examined DFIG controller signals spectra. Furthermore, it is shown that wide-band rotor electrical fault related spectral signatures in the controller signals carry considerable diagnostic potential for recognition of rotor electrical faults.
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    Stator Electrical Fault Detection in DFIGs Using Wide-Band Analysis of the Embedded Signals From the Controllers
    (Ieee-Inst Electrical Electronics Engineers Inc, 2021) Sarma, Nur; Tuohy, Paul M.; Djurovic, Sinisa
    This article presents a novel study of stator electrical faults detection using the wide-band spectral signatures in the controller signals of doubly fed induction generators (DFIGs). The possible wide-band spectral content of the controller signals are first defined with a set of analytical equations in order to characterize the wide-band spectral signatures and their correlation to operating conditions including stator electrical faults. A DFIG harmonic model and laboratory test-rig are used to validate the derived equations. The calculated, simulated and experimental results are in good agreement. Furthermore, it is shown that the wide-band stator electrical fault related spectral signatures carry considerable diagnostic potential for recognition of stator electrical faults, and therefore, can potentially be used to advance controller embedded fault detection techniques.