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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Abstract

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
JournalSustainability
Volume13
Issue number2
Number of pages10
ISSN2071-1050
DOIs
Publication statusPublished - 2021

Keywords

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

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