An Effective Approach for Rotor Electrical Asymmetry Detection in Wind Turbine DFIGs

Sinisa Durovic, Christopher J. Crabtree, Raed Ibrahim, Simon Watson

    Research output: Contribution to journalArticlepeer-review


    Determining the magnitude of particular fault
    signature components (FSCs) generated by wind turbine
    (WT) faults from current signals has been used as an
    effective way to detect early abnormalities. However, the
    WT current signals are time-varying due to the constantly
    varying generator speed. The WT frequently operates with
    the generator close to synchronous speed, resulting in
    FSCs manifesting themselves in the vicinity of the supply
    frequency and its harmonics, making their detection more
    challenging. To address this challenge, the detection of rotor
    electrical asymmetry in WT doubly-fed induction generators
    (DFIGs), indicative of common winding, brush gear
    or high resistance connection faults, has been investigated
    using a test-rig under three different driving conditions,
    and then an effective extended Kalman filter (EKF) based
    method is proposed to iteratively estimate the FSCs and
    track their magnitude. The proposed approach has been
    compared with a continuous wavelet transform (CWT) and
    an iterative localized discrete Fourier-transform (IDFT). The
    experimental results demonstrate that the CWT and IDFT
    algorithms fail to track the FSCs at low load operation
    near synchronous speed. In contrast, the EKF was more
    successful in tracking the FSCs magnitude in all operating
    conditions, unambiguously determining the severity of the
    faults over time and providing significant gains in both
    computational efficiency and accuracy of fault diagnosis.
    Original languageEnglish
    Pages (from-to)1-10
    JournalIEEE Transactions on Industrial Electronics
    Publication statusPublished - 19 Mar 2018


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