An advanced structural health monitoring IoT platform for offshore wind turbine blades
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 blad...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | Manufacturing Review |
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| Online Access: | https://mfr.edp-open.org/articles/mfreview/full_html/2025/01/mfreview240064/mfreview240064.html |
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| author | Zhou Xingguo Tian Yankang Qin Yi Charitidis Costas A. Milickovic Tanja K. Termine Stefania |
| author_facet | Zhou Xingguo Tian Yankang Qin Yi Charitidis Costas A. Milickovic Tanja K. Termine Stefania |
| author_sort | Zhou Xingguo |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4993f5d816074a7c8bd7ac48baf4023a |
| institution | Kabale University |
| issn | 2265-4224 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Manufacturing Review |
| spelling | doaj-art-4993f5d816074a7c8bd7ac48baf4023a2025-08-20T03:53:51ZengEDP SciencesManufacturing Review2265-42242025-01-01121210.1051/mfreview/2025008mfreview240064An advanced structural health monitoring IoT platform for offshore wind turbine bladesZhou Xingguo0https://orcid.org/0000-0001-8542-7510Tian Yankang1Qin Yi2Charitidis Costas A.3Milickovic Tanja K.4Termine Stefania5Centre for Precision Manufacturing, Dept. of DMEM, University of StrathclydeInnova Nanojet Technologies LtdCentre for Precision Manufacturing, Dept. of DMEM, University of StrathclydeSchool of Chemical Engineering, National Technical University of AthensSchool of Chemical Engineering, National Technical University of AthensSchool of Chemical Engineering, National Technical University of AthensWind 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.https://mfr.edp-open.org/articles/mfreview/full_html/2025/01/mfreview240064/mfreview240064.htmloffshore wind turbinesiot platformstructural health monitoringblade monitoringqrs sensorcloud databasewind energyrenewable energy |
| spellingShingle | Zhou Xingguo Tian Yankang Qin Yi Charitidis Costas A. Milickovic Tanja K. Termine Stefania An advanced structural health monitoring IoT platform for offshore wind turbine blades Manufacturing Review offshore wind turbines iot platform structural health monitoring blade monitoring qrs sensor cloud database wind energy renewable energy |
| title | An advanced structural health monitoring IoT platform for offshore wind turbine blades |
| title_full | An advanced structural health monitoring IoT platform for offshore wind turbine blades |
| title_fullStr | An advanced structural health monitoring IoT platform for offshore wind turbine blades |
| title_full_unstemmed | An advanced structural health monitoring IoT platform for offshore wind turbine blades |
| title_short | An advanced structural health monitoring IoT platform for offshore wind turbine blades |
| title_sort | advanced structural health monitoring iot platform for offshore wind turbine blades |
| topic | offshore wind turbines iot platform structural health monitoring blade monitoring qrs sensor cloud database wind energy renewable energy |
| url | https://mfr.edp-open.org/articles/mfreview/full_html/2025/01/mfreview240064/mfreview240064.html |
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