Real-time monitoring, fault prediction and health management for offshore wind turbine systems

Zhiwei Gao; Peter Odgaard

doi:10.1016/j.renene.2023.119258

Real-time monitoring, fault prediction and health management for offshore wind turbine systems

Zhiwei Gao^*, Peter Odgaard

^*Corresponding author for this work

Research output: Contribution to journal › Editorial › peer-review

37 Citations (Scopus)

100 Downloads (Pure)

Original language	English
Article number	119258
Journal	Renewable Energy
Volume	218
Early online date	14 Sept 2023
DOIs	https://doi.org/10.1016/j.renene.2023.119258
Publication status	Published - 1 Dec 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1016/j.renene.2023.119258

Offshore wind energy systems-editorial-SKZWAccepted author manuscript, 204 KBLicence: CC BY-NC-ND

Cite this

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title = "Real-time monitoring, fault prediction and health management for offshore wind turbine systems",

author = "Zhiwei Gao and Peter Odgaard",

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T1 - Real-time monitoring, fault prediction and health management for offshore wind turbine systems

AU - Gao, Zhiwei

AU - Odgaard, Peter

PY - 2023/12/1

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UR - https://www.scopus.com/pages/publications/85170518034

U2 - 10.1016/j.renene.2023.119258

DO - 10.1016/j.renene.2023.119258

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VL - 218

JO - Renewable Energy

JF - Renewable Energy

M1 - 119258

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Real-time monitoring, fault prediction and health management for offshore wind turbine systems

UN SDGs

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