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

Complexity

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

Philosophy

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