Issue |
Manufacturing Rev.
Volume 12, 2025
Advanced Manufacturing Research – Latest Developments
|
|
---|---|---|
Article Number | 12 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/mfreview/2025008 | |
Published online | 25 April 2025 |
Original Article
An advanced structural health monitoring IoT platform for offshore wind turbine blades
1
Centre for Precision Manufacturing, Dept. of DMEM, University of Strathclyde, G1 1XJ Glasgow, United Kingdom
2
Innova Nanojet Technologies Ltd, Glasgow, United Kingdom
3
School of Chemical Engineering, National Technical University of Athens, Athens, Greece GR-157 73
* e-mail: xingguo.zhou@strath.ac.uk; qin.yi@strath.ac.uk
Received:
6
November
2024
Accepted:
15
March
2025
Wind energy is renewable and is an essential ingredient in the move towards carbon neutrality and net zero emissions Compared with onshore wind turbines, offshore wind turbines generally experience higher wind speed, thus producing more electricity. However, the increasing dimensions of turbine blades and demands in economic requirements of wind turbines' life cycles, together with the harsh marine environment, including high winds, wave-induced vibrations, sea and rain corrosion and erosion, pose challenges for structural integrity, operational efficiency and maintenance cost. This paper presents a novel Internet of Things (IoT) platform for structural health monitoring (SHM) of the offshore wind turbine's key components, the wind turbine blades, taking the design and manufacturing of turbine blades into account. This research focuses on developing a comprehensive, real-time monitoring system that utilises advanced sensor networks and edge computing, empowering advanced predictive algorithms to strengthen in-time maintenance of turbine blades, improving operational efficiency and reducing maintenance cost.
Key words: Offshore wind turbines / IoT platform / structural health monitoring / blade monitoring / QRS sensor / cloud database / wind energy / renewable energy
© X. Zhou et al., Published by EDP Sciences 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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