Overview of Condition Monitoring Technology for Variable-Speed Offshore Wind Turbines

Yuankui Wang, Hai Liu, Qingyuan Li, Xinchen Wang, Zizhao Zhou, Haiyang Xu (), Dahai Zhang and Peng Qian ()
Additional contact information
Yuankui Wang: Ocean College, Zhejiang University, Zhoushan 316021, China
Hai Liu: Ocean College, Zhejiang University, Zhoushan 316021, China
Qingyuan Li: Ocean College, Zhejiang University, Zhoushan 316021, China
Xinchen Wang: Ocean College, Zhejiang University, Zhoushan 316021, China
Zizhao Zhou: Ocean College, Zhejiang University, Zhoushan 316021, China
Haiyang Xu: Ocean College, Zhejiang University, Zhoushan 316021, China
Dahai Zhang: Ocean College, Zhejiang University, Zhoushan 316021, China
Peng Qian: Ocean College, Zhejiang University, Zhoushan 316021, China

Energies, 2025, vol. 18, issue 5, 1-24

Abstract: With the increasing complexity of offshore wind turbine structures and the rapid expansion of wind power projects, efficient, reliable, and robust fault diagnosis and condition monitoring methods have become crucial for effective operation and maintenance management. Wind turbine condition monitoring plays a pivotal role in improving operational efficiency. However, most existing fault diagnosis techniques based on vibration signals are designed for rotating mechanical equipment operating at constant speeds. In contrast, offshore wind turbines experience continuously varying speeds, especially during start-up, shutdown, and under fluctuating wind conditions, leading to rotor speed variations that complicate monitoring. This paper presents a comprehensive analysis of the vibration and fault characteristics of key components in the main drivetrain of offshore wind turbines, with a particular focus on monitoring non-stationary (variable speed) operations. Unlike conventional approaches, this work specifically addresses the challenges posed by the dynamic operating conditions of offshore wind turbines, providing insights into multi-component vibration signal feature extraction and fault diagnosis under variable-speed scenarios. The comparative analysis offered in this paper highlights the limitations of current methods and outlines key directions for future research, emphasizing practical solutions for fault diagnosis and condition monitoring in offshore wind turbine operations under variable-speed conditions. This study not only fills a gap in the current literature but also provides valuable guidance for enhancing the reliability and efficiency of offshore wind turbine maintenance.

Keywords: nonstationary signal; offshore wind turbine; multi-componenent signal decomposition; order tracking; time–frequency ridge extraction (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: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/5/1026/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/5/1026/ (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:18:y:2025:i:5:p:1026-:d:1595587

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 ().