Distributed Intelligent System Architecture for UAV-Assisted Monitoring of Wind Energy Infrastructure
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Semi-Supervised Defect Detection via Conditional Diffusion and CLIP-Guided Noise Filtering
How Good Are Synthetic Requirements ? Evaluating LLM-Generated Datasets for AI4RE
SteelBlastQC: Shot-blasted Steel Surface Dataset with Interpretable Detection of Surface Defects
Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly Detections
ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation
Predicting Performance of Object Detection Models in Electron Microscopy Using Random Forests
토론
이 논문과 연결된 포럼 글이 아직 없습니다.