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Öğe DFIG current and controller signals' angular shaft misalignment signature - an experimental case study(Ieee, 2020) Wang, Yingzhao; Sarma, Nur; Mohammed, Anees; Djurovic, Sinisawith the continuous increase in wind turbine generator size the monitoring and diagnosis of drive train shaft misalignment is of growing importance, as this condition contributes to as much as 30% of turbine's downtime. Machine current signature analysis has been widely investigated in conventional machinery as a non-invasive diagnostic tool for shaft misalignment, via spectrum analysis of the stator current signal. This paper reports a practical case study of misalignment fault signature manifestation in the doubly-fed induction generator (DFIG) controller signals spectra, with a view to assessing the feasibility of low cost and non-invasive controller signal analysis based misalignment diagnosis. The study employs a laboratory test rig to undertake a series of tests to analyze the sensitivity of controller signals to a specific angular misalignment condition, and hence evaluate and characterize the manifestation of its spectral signatures.Öğe Double Fed Induction Generator Shaft Misalignment Monitoring by FBG Frame Strain Sensing(Ieee-Inst Electrical Electronics Engineers Inc, 2020) Wang, Yingzhao; Mohammed, Anees; Sarma, Nur; Djurovic, SinisaThis study explores the potential for using FBG strain sensing to enable recognition of the shaft misalignment condition in electric machine drivetrains through observation of machine frame distributed relative strain. The sensing principles, design and installation methods of the proposed technique are detailed in the paper. The scheme was applied on a purpose built wind turbine generator representative laboratory test rig and its performance evaluated in an extensive experimental study involving a range of healthy and misaligned shaft operating conditions. The obtained experimental data demonstrate the reported method's capability to enable recognition of generator shaft misalignment conditions and thus its health monitoring. Finally, it is shown that the thermal variation of the generator frame structure inherent to its operation, combined with the FBG sensor intrinsic thermo-mechanical cross sensitivity, has no detrimental impact on the fidelity and usability of the observed strain measurements.Öğe 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, SinisaThis 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.