Issue |
E3S Web Conf.
Volume 194, 2020
2020 5th International Conference on Advances in Energy and Environment Research (ICAEER 2020)
|
|
---|---|---|
Article Number | 03006 | |
Number of page(s) | 6 | |
Section | Power Engineering and Power Generation Technology | |
DOI | https://doi.org/10.1051/e3sconf/202019403006 | |
Published online | 15 October 2020 |
Gearbox Fault Prediction of Wind Turbine Based on Improved NEST Model
Datang Northeast Electric Power Test & Research Institute Co., Ltd, Thermal Automation Department, 130000 Changchun, China
This paper studies a fault prediction method for wind turbine gearbox. It uses grey relation analysis to get modeling variables, and makes sample data getting good integrity and redundancy by similarity analysis. Thus it gets the reduced process memory matrix, and trains the improved nonlinear state estimation (NEST) model. When the gearbox fails, the model residual will exceed the threshold value, and the model will give an early warning. Combined with the actual operation data of a wind turbine, the effectiveness and accuracy of the improved model are verified.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.