An Approach of Quantifying Gear Fatigue Life for Wind Turbine Gearboxes Using Supervisory Control and Data Acquisition Data

Yingning Qiu, Lang Chen, Yanhui Feng and Yili Xu
Additional contact information
Yingning Qiu: School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Lang Chen: School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Yanhui Feng: School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Yili Xu: Zhejiang Windey Ltd. by Share Ltd, 22F, Building A, the West Lake International Plaza S&T, No. 391, Wen’er Road, Hangzhou 310012, China

Energies, 2017, vol. 10, issue 8, 1-21

Abstract: Quantifying wind turbine (WT) gearbox fatigue life is a critical problem for preventive maintenance when unsolved. This paper proposes a practical approach that uses ten minutes’ average wind speed of Supervisory Control and Data Acquisition (SCADA) data to quantify a WT gearbox’s gear fatigue life. Wind turbulence impacts on gearbox fatigue are studied thoroughly. Short-term fatigue assessment for the gearbox is then performed using linear fatigue theory by considering WT responses under external and internal excitation. The results shows that for a three stage gearbox, the sun gear in the first stage and pinions in the 2nd and 3rd stage are the most vulnerable parts. High mean wind speed, especially above the rated range, leads to a high risk of gearbox fatigue damage. Increase of wind turbulence may not increase fatigue damage as long as a WT has an instant response to external excitation. An approach of using SCADA data recorded every ten minutes to quantify gearbox long-term damages is presented. The calculation results show that the approach effectively presents gears’ performance degradation by quantifying their fatigue damage. This is critical to improve WT reliability and meaningful for WT gearbox fatigue assessment theory. The result provides useful tools for future wind farm prognostic maintenance.

Keywords: wind turbine (WT); fatigue life; gearbox; supervisory control and data acquisition (SCADA) data (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: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/1996-1073/10/8/1084/pdf (application/pdf)
https://www.mdpi.com/1996-1073/10/8/1084/ (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:10:y:2017:i:8:p:1084-:d:105773

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 ().