Research and Development of AI-Enabled Adaptive Imaging System for Renewable Energy

With the large-scale development of the wind power industry, higher requirements have been put forward for intelligent and efficient operation and maintenance. This article focuses on the application of image recognition technology in the lifting and operation of wind farm towers, and designs and deploys a system solution that integrates image acquisition, data transmission, and intelligent recognition. By comparing core indicators such as safety accident rate, response time, repair efficiency, and cost-effectiveness before and after implementation, the significant effects of the system in improving safety management level, reducing operation and maintenance costs, and shortening fault handling cycles have been verified. The study also shows that the optimized image acquisition device is superior to traditional equipment in terms of energy consumption, image quality, and operational stability, and has good on-site adaptability and promotion prospects. This study provides a feasible path and theoretical support for the wind power industry to achieve intelligent operation and maintenance.

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Published
2025-04-25
DOI
https://doi.org/10.1109/nesp65198.2025.11040768
Primary Topic
Advanced Technologies in Various Fields
Type
article
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Research and Development of AI-Enabled Adaptive Imaging System for Renewable Energy

Qianqian Song, Shibiao Fang, Liping Liu, Huajian Zhou
Advanced Technologies in Various Fields
article

Research and Development of AI-Enabled Adaptive Imaging System for Renewable Energy

Qianqian Song, Shibiao Fang, Liping Liu, Huajian Zhou
article en

Abstract

With the large-scale development of the wind power industry, higher requirements have been put forward for intelligent and efficient operation and maintenance. This article focuses on the application of image recognition technology in the lifting and operation of wind farm towers, and designs and deploys a system solution that integrates image acquisition, data transmission, and intelligent recognition. By comparing core indicators such as safety accident rate, response time, repair efficiency, and cost-effectiveness before and after implementation, the significant effects of the system in improving safety management level, reducing operation and maintenance costs, and shortening fault handling cycles have been verified. The study also shows that the optimized image acquisition device is superior to traditional equipment in terms of energy consumption, image quality, and operational stability, and has good on-site adaptability and promotion prospects. This study provides a feasible path and theoretical support for the wind power industry to achieve intelligent operation and maintenance.

Shenzhen University (CN)
Affordable and clean energy
Openalex Percentile: Top 93%
Advanced Technologies in Various Fields
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Research and Development of AI-Enabled Adaptive Imaging System for Renewable Energy — Qianqian Song, Shibiao Fang, et al. · (2025) | TGRS Research Map | TGRS