Wind Turbine Gearbox Diagnosis Based on Stator Current

Idris Issaadi (), Kamel Eddine Hemsas and Abdenour Soualhi ()
Additional contact information
Idris Issaadi: LAS Laboratory, Department of Electrical Engineering, Faculty of Technology, Ferhat Abbas University Setif-1, Campus El Bez, Setif 19137, Algeria
Kamel Eddine Hemsas: LAS Laboratory, Department of Electrical Engineering, Faculty of Technology, Ferhat Abbas University Setif-1, Campus El Bez, Setif 19137, Algeria
Abdenour Soualhi: Laspi, University of Jean Monnet, 20 Avenue de Paris, 42300 Roanne, France

Energies, 2023, vol. 16, issue 14, 1-19

Abstract: Early detection of faults in wind energy systems can reduce downtime, operating, and maintenance costs while increasing productivity. This paper proposes a method based on the analysis of generator stator current signals to detect faults in a wind turbine gearbox equipped with a doubly fed induction generator (DFIG). A localized parameter model was established to simulate the vibratory response of a two-stage gear system under healthy and faulty conditions. The simulation was performed in the MATLAB/Simulink environment. The results include a detailed analysis of the mechanical part of the gearbox, highlighting mesh stiffness, output speed, and accelerations. Additionally, the electrical part was evaluated based on the current supplied by the doubly fed induction generator. The results were presented in the case of healthy gears and in the presence of faults such as a broken or cracked tooth. Fast Fourier transform (FFT) analysis was employed to detect gear defects in the stator current signal. The presence of a crack or broken tooth in the gearbox induces modulation of the DFIG stator current signals according to the shaft frequencies corresponding to the faulty gear. These findings provide a preliminary basis for the detection and diagnosis of this type of failure.

Keywords: current signal; doubly fed induction generator (DFIG); fault detection; gearbox; two-stage spur gear system; wind turbine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/14/5286/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/14/5286/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:14:p:5286-:d:1190872

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().