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.
|Title of host publication||IEEE|
|Publication status||Published - 23 Aug 2020|
|Event|| 2020 IEEE International Conference on Electrical Machines - Virtual|
Duration: 23 Aug 2020 → 26 Aug 2020
|Conference||2020 IEEE International Conference on Electrical Machines|
|Abbreviated title||IEEE ICEM2020|
|Period||23/08/20 → 26/08/20|