Fault Detection of Wind Turbine Pitch System Based on Multiclass Optimal Margin Distribution Machine
Joint Authors
Tang, Mingzhu
Wu, Huawei
Kuang, Zijie
Zhao, Qi
Yang, Xu
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In response to the unbalanced sample categories and complex sample distribution of the operating data of the pitch system of the wind turbine generator system, this paper proposes a method for fault detection of the pitch system of the wind turbine generator system based on the multiclass optimal margin distribution machine.
In this method, the power output of the wind turbine generator system is used as the main status parameter, and the operating data history of the wind turbine generator system in the wind power supervisory control and data acquisition (SCADA) system is subject to correlation analysis with the Pearson correlation coefficient, to eliminate the features that have low correlation with the power output status parameter.
Secondary analysis is performed to the remaining features, thus reducing the number and complexity of samples.
Datasets are divided into the training set for training of the multiclass optimal margin distribution machine fault detection model and test set for testing.
Experimental verification was carried out with the operating data of one wind farm in China.
Experimental results show that, compared with other support vector machines, the proposed method has higher fault detection accuracy and precision and lower false-negative rate and false-positive rate.
American Psychological Association (APA)
Tang, Mingzhu& Kuang, Zijie& Zhao, Qi& Wu, Huawei& Yang, Xu. 2020. Fault Detection of Wind Turbine Pitch System Based on Multiclass Optimal Margin Distribution Machine. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1193693
Modern Language Association (MLA)
Tang, Mingzhu…[et al.]. Fault Detection of Wind Turbine Pitch System Based on Multiclass Optimal Margin Distribution Machine. Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1193693
American Medical Association (AMA)
Tang, Mingzhu& Kuang, Zijie& Zhao, Qi& Wu, Huawei& Yang, Xu. Fault Detection of Wind Turbine Pitch System Based on Multiclass Optimal Margin Distribution Machine. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1193693
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193693