The continuous growth in wind turbine power ratings and numbers has led to increased demands in inspection and maintenance due to the more significant financial and operational consequences of unexpected wind turbine failure. The fact that wind farms are commonly located at remote sites with potentially poor accessibility means it is necessary to reduce the need for corrective maintenance through evolution to preventive and prognostic maintenance activities. Prognostic repair schedules can be employed in order to optimise maintenance and contribute to the minimisation of the overall operational costs of wind farms. The present study presents the development and qualitative evaluation of remote condition monitoring methodologies for the evaluation of the wind turbine power electronics and gearboxes. The failures of power converter and gearbox components result in significant wind turbine downtime and associated repair costs. Effective condition monitoring can enable the timely diagnosis of faults in order to prevent unexpected failures and loss of electricity production, contributing towards a noteworthy increase the reliability, availability, maintainability and safety (RAMS) of wind farms. Within this study two customised test rigs have been employed to simulate various of faults and assess the capability of RCM in diagnosing this fault effectively. In addition, field measurements have been carried out and correlated to the findings of the test rig experiments. In this study, it has been possible to identify these variables qualitatively, but the quantitative investigation is still pending and will be most likely the subject of several future studies in this field. The present thesis provides a compact summary of the analysis of the key findings of the experimental work performed within the context of the OPTIMUS FP7 European collaborative project.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:742631 |
| Date | January 2018 |
| Creators | Hajiabady, Siavash |
| Publisher | University of Birmingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.bham.ac.uk//id/eprint/8121/ |
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