A Human-Cyber-Physical System toward Intelligent Wind Turbine Operation and Maintenance

Xiao Chen, Martin A. Eder, Asm Shihavuddin, Dan Zheng*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    This work proposes a novel concept for an intelligent and semi-autonomous human-cyber-physical system (HCPS) to operate future wind turbines in the context of Industry 5.0 technologies. The exponential increase in the complexity of next-generation wind turbines requires artificial intelligence (AI) to operate the machines efficiently and consistently. Evolving the current Industry 4.0 digital twin technology beyond a sole aid for the human decision-making process, the digital twin in the proposed system is used for highly effective training of the AI through machine learning. Human intelligence (HI) is elevated to a supervisory level, in which high-level decisions made through a human–machine interface break the autonomy, when needed. This paper also identifies and elaborates key enabling technologies (KETs) that are essential for realizing the proposed HCPS.
    Original languageEnglish
    Article number561
    Issue number2
    Number of pages10
    Publication statusPublished - 2021


    • WInd turbine
    • Humn intelligence
    • Artificial intelligence
    • Machine learning
    • Digital twin
    • Industry 5.0


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