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Yazar "Wang, Yingzhao" seçeneğine göre listele

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    DFIG current and controller signals' angular shaft misalignment signature - an experimental case study
    (Ieee, 2020) Wang, Yingzhao; Sarma, Nur; Mohammed, Anees; Djurovic, Sinisa
    with 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.
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    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, Sinisa
    This 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.

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