Thesis
Thermal modelling of wind turbine gearboxes for condition monitoring
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2025
- Thesis identifier
- T17339
- Person Identifier (Local)
- 201694012
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- This thesis explores wind farm reliability research which identifies the gearbox as having the most detrimental influence on wind turbine (WT) reliability. This research brings together theoretical thermal modelling, experimental research, and machine learning data analysis applied specifically for WT gearbox condition monitoring. Existing condition monitoring techniques were explored and many of these data driven models required significant amounts of historical data. A thermal model was created for a experimental WT test rig and faults were simulated in the form of losses to analyse changes in thermal behaviour. The design of the WT test rig experimental data acquisition set-up is outlined and the results used to validate the thermal model. Inverse thermal modelling was then applied to real life WT data to estimate changes in losses at particular components, between when a gearbox is healthy, or is one month from a known failure. It was found that there was a potential to detect failure, but efficacy is reduced when the fault is not located near a sensor. However, when carrying out weighting analysis, it was found that combining thermal model results with temperature data, losses could prove more effective in health classification. WT gearbox reliability analysis was carried out on a population of WTs in relation to the WT power train configuration, comparing the reliability of the gearbox when in a Doubly Fed Induction Generator (DFIG) WT or a Permanent Magnet Generator (PMG) WT. The results of the analysis presented DFIG WT as having worse overall gearbox reliability. This led to the hypothesis that the operation in relation to the grid could have an effect on gearbox loading, fatigue and thus reliability.
- Advisor / supervisor
- McDonald, Alasdair S.
- Carroll, James
- Resource Type
- DOI
- Embargo Note
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File | 2025-12-01 | Private |