Kyoo-seon Park
Simulation based approach to predict vertical axis wind turbine faults using computational fluid dynamics.
Park, Kyoo-seon; Asim, Taimoor; Mishra, Rakesh
Abstract
Use of on-line fault detection techniques is integral to successful operation and maintenance of a wind turbine installation. The deployment of condition monitoring systems needs to be structured and sensitive to likely faults that may occur. In this work effects of blade faults have been simulated to understand sensitivity of blade faults on torque output. It is expected that this will help in developing a blade related condition monitoring strategy for a wind turbine system. It has been seen that instantaneous torque is a strong function of any blade imbalance and the torque output can be used successfully to identify initiation of blade imbalance related effects.
Citation
PARK, K.-S., ASIM, T. and MISHRA, R. 2012. Simulation based approach to predict vertical axis wind turbine faults using computational fluid dynamics. Presented at 1st Through-life engineering services international conference 2012 (TESConf 2012), 5-6 November 2012, Cranfield, UK.
Presentation Conference Type | Conference Paper (unpublished) |
---|---|
Conference Name | 1st Through–life engineering services international conference 2012 (TESConf 2012) |
Start Date | Nov 5, 2012 |
End Date | Nov 6, 2012 |
Deposit Date | Jun 29, 2021 |
Publicly Available Date | Jun 29, 2021 |
Peer Reviewed | Peer Reviewed |
Keywords | Condition monitoring; Computational fluid dynamics; Sliding mesh; Vertical axis wind turbines |
Public URL | https://rgu-repository.worktribe.com/output/872398 |
Files
PARK 2012 Simulation based approach
(1.1 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
You might also like
Start-up dynamics of vertical axis wind turbines: a review.
(2023)
Journal Article
Hydrodynamic characterisation of fire sprinkler system of a passenger railroad car.
(2023)
Journal Article
Downloadable Citations
About OpenAIR@RGU
Administrator e-mail: publications@rgu.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search