Concepedia

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

Xiao Chen, M. Eder, ASM Shihavuddin, Dan Zheng

Sustainability · 2021 · 111 citations · 16 references

Open access

TL;DR

Next‑generation wind turbines are becoming increasingly complex, demanding AI to operate them efficiently and consistently. The study proposes an intelligent, semi‑autonomous human‑cyber‑physical system for future wind turbines and identifies key enabling technologies required for its realization. The HCPS uses an Industry 4.0 digital twin to train AI via machine learning, while human intelligence supervises high‑level decisions through a human‑machine interface that can override autonomy when necessary.

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.