Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE
Joint Authors
Lu, Ming
Duan, Hao
Sun, Yongteng
Wang, Jinyu
Wang, Cheng
Chen, Zuguo
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
After fault occurs, the fault diagnosis of wind turbine system is required accurately and quickly.
This paper presents a fault diagnostic method for open-circuit faults in the converter of permanent magnet synchronous generator drive for the wind turbine.
To avoid misjudgement or missed judgement caused by improper thresholds, the proposed method applies Local Mean Decomposition and Multiscale Entropy into the converter of wind power system fault diagnosis for the first time.
This paper uses a novel multiclass support vector machine to classify the faults hardly diagnosed by other methods.
Simulation results show that the method has the characteristics of high adaptability, high accuracy, and less diagnosis time.
American Psychological Association (APA)
Duan, Hao& Lu, Ming& Sun, Yongteng& Wang, Jinyu& Wang, Cheng& Chen, Zuguo. 2020. Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142376
Modern Language Association (MLA)
Duan, Hao…[et al.]. Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1142376
American Medical Association (AMA)
Duan, Hao& Lu, Ming& Sun, Yongteng& Wang, Jinyu& Wang, Cheng& Chen, Zuguo. Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142376
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142376