Publication details for Dr Christopher CrabtreeZappalá, D., Sarma, N., Djurović, S., Crabtree, C. J., Mohammad, A. & Tavner, P. J. (2019). Electrical & Mechanical Diagnostic Indicators of Wind Turbine Induction Generator Rotor Faults. Renewable Energy 131: 14-24.
- Publication type: Journal Article
- ISSN/ISBN: 0960-1481
- DOI: 10.1016/j.renene.2018.06.098
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
In MW-sized wind turbines, the most widely-used generator is the wound rotor induction machine, with a partially-rated voltage source converter connected to the rotor. This generator is a significant cause of wind turbine fault modes. In this paper, a harmonic time-stepped generator model is applied to derive wound rotor induction generator electrical & mechanical signals for fault measurement, and propose simple closed-form analytical expressions to describe them. Predictions are then validated with tests on a 30 kW induction generator test rig. Results show that generator rotor unbalance produces substantial increases in the side-bands of supply frequency and slotting harmonic frequencies in the spectra of current, power, speed, mechanical torque and vibration measurements. It is believed that this is the first occasion in which such comprehensive approach has been presented for this type of machine, with healthy & faulty conditions at varying loads and rotor faults. Clear recommendations of the relative merits of various electrical & mechanical signals for detecting rotor faults are given, and reliable fault indicators are identified for incorporation into wind turbine condition monitoring systems. Finally, the paper proposes that fault detectability and reliability could be improved by data fusion of some of these electrical & mechanical signals.