Article

Grey-based failure mode and effect analysis of floating offshore wind turbines

Ocean Engineering

Kong, Xiangyu ; Li, He; Guedes Soares, C. — 2026 — Elvesier

Key information

Authors:

Kong, Xiangyu (Xiangyu Kong); Li, He (He Li); Guedes Soares, C. (Carlos Guedes Soares)

Published in

January 15, 2026

Abstract

This paper proposes a Grey-based Failure Mode and Effect Analysis (G-FMEA) approach to complete the failure analysis of floating offshore wind turbines. A multi-level weighting method is first developed to evaluate interactions between systems and components. A Grey Priority Number is then determined to calculate and rank the hazard of failure items based on the Grey System Theory. The approach identifies critical items of floating offshore wind turbines, including eight components, 15 associated failure modes, and 24 root failure causes. Corresponding recommendations are suggested to mitigate their likelihood and impact on the entire wind turbine. A comparative analysis confirms the effectiveness and superiority of the proposed method over the existing ones. Overall, the proposed G-FMEA approach contributes to the avoidance of failures and the maintenance scheduling of offshore wind turbines and wind farms.

Publication details

Authors in the community:

Publication version

VoR - Version of Record

Publisher

Elvesier

Link to the publisher's version

https://www.sciencedirect.com/science/article/pii/S0029801825030367?via%3Dihub

Title of the publication container

Ocean Engineering

First page or article number

123353

Last page

Part 3

Volume

343

DOI

10.1016/j.oceaneng.2025.123353

Fields of Science and Technology (FOS)

other-engineering-and-technologies - Other engineering and technologies

Keywords

  • Floating offshore wind turbine
  • Failure analysis
  • Failure Mode and Effect Analysis
  • Grey theory

Publication language (ISO code)

eng - English

Rights type:

Open access

Financing entity

Fundação para a Ciência e a Tecnologia

Identifier for the funding entity: https://doi.org/10.13039/501100001871

Type of identifier of the funding entity: Crossref Funder

Number for the project, award or grant: UIDB-UIDP-00134-2020