Distributed Intelligent System Architecture for UAV-Assisted Monitoring of Wind Energy Infrastructure
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866912153702760448 |
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| author | Svystun, Serhii Melnychenko, Oleksandr Radiuk, Pavlo Savenko, Oleg Lysyi, Andrii |
| author_facet | Svystun, Serhii Melnychenko, Oleksandr Radiuk, Pavlo Savenko, Oleg Lysyi, Andrii |
| contents | With the rapid development of green energy, the efficiency and reliability of wind turbines are key to sustainable renewable energy production. For that reason, this paper presents a novel intelligent system architecture designed for the dynamic collection and real-time processing of visual data to detect defects in wind turbines. The system employs advanced algorithms within a distributed framework to enhance inspection accuracy and efficiency using unmanned aerial vehicles (UAVs) with integrated visual and thermal sensors. An experimental study conducted at the "Staryi Sambir-1" wind power plant in Ukraine demonstrates the system's effectiveness, showing a significant improvement in defect detection accuracy (up to 94%) and a reduction in inspection time per turbine (down to 1.5 hours) compared to traditional methods. The results show that the proposed intelligent system architecture provides a scalable and reliable solution for wind turbine maintenance, contributing to the durability and performance of renewable energy infrastructure. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_09387 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributed Intelligent System Architecture for UAV-Assisted Monitoring of Wind Energy Infrastructure Svystun, Serhii Melnychenko, Oleksandr Radiuk, Pavlo Savenko, Oleg Lysyi, Andrii Robotics Artificial Intelligence Systems and Control I.4.8; I.2.10; I.5.4; I.2.9 With the rapid development of green energy, the efficiency and reliability of wind turbines are key to sustainable renewable energy production. For that reason, this paper presents a novel intelligent system architecture designed for the dynamic collection and real-time processing of visual data to detect defects in wind turbines. The system employs advanced algorithms within a distributed framework to enhance inspection accuracy and efficiency using unmanned aerial vehicles (UAVs) with integrated visual and thermal sensors. An experimental study conducted at the "Staryi Sambir-1" wind power plant in Ukraine demonstrates the system's effectiveness, showing a significant improvement in defect detection accuracy (up to 94%) and a reduction in inspection time per turbine (down to 1.5 hours) compared to traditional methods. The results show that the proposed intelligent system architecture provides a scalable and reliable solution for wind turbine maintenance, contributing to the durability and performance of renewable energy infrastructure. |
| title | Distributed Intelligent System Architecture for UAV-Assisted Monitoring of Wind Energy Infrastructure |
| topic | Robotics Artificial Intelligence Systems and Control I.4.8; I.2.10; I.5.4; I.2.9 |
| url | https://arxiv.org/abs/2412.09387 |