Indicative Fault Diagnosis of Wind Turbine Generator Bearings Using Tower Sound and Vibration†
AbstractThe idea of indicative fault diagnosis based on measuring the wind turbine tower sound and vibration is presented. It had been reported by a wind farm operator that a major fault on the generator bearing causes shock and noise to be heard from the bottom of the wind turbine tower. The work in this paper was conceived to test whether tower top faults could be identified by taking simple measurements at the tower base. Two accelerometers were attached inside the wind turbine tower, and vibration data was collected while the wind turbine was in operation. Tower vibration signals were analyzed using Empirical Mode Decomposition and the outcomes were correlated with the vibration signals acquired directly from the generator bearings. It is shown that the generator bearing fault signatures were present in the vibrations from the tower. The results suggest that useful condition monitoring of nacelle components can be done even when there is no condition monitoring system installed on the generator bearings, as is often the case for older wind turbines. In the second part of the paper, acoustic measurements from a healthy and a faulty wind turbine are shown. The preliminary analysis suggests that the generator bearing fault increases the overall sound pressure level at the bottom of the tower, and is not buried in the background noise. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Mollasalehi, E.; Wood, D.; Sun, Q. Indicative Fault Diagnosis of Wind Turbine Generator Bearings Using Tower Sound and Vibration. Energies 2017, 10, 1853.
Mollasalehi E, Wood D, Sun Q. Indicative Fault Diagnosis of Wind Turbine Generator Bearings Using Tower Sound and Vibration. Energies. 2017; 10(11):1853.Chicago/Turabian Style
Mollasalehi, Ehsan; Wood, David; Sun, Qiao. 2017. "Indicative Fault Diagnosis of Wind Turbine Generator Bearings Using Tower Sound and Vibration." Energies 10, no. 11: 1853.