Bucket hydropower is one of the most widely used hydropower generation equipment, and the YOLO algorithm is an efficient object detection technology. The purpose of this paper is to combine the two to construct an unattended intelligent hydropower navigation device, which can not only reduce energy consumption, but also realize real-time and accurate monitoring of the waterway. By combining the bucket turbine with the solar power supply system, this paper effectively avoids the energy waste and environmental pollution caused by the battery on the one hand and ensures the stability and durability of the power supply on the other hand. At the same time, the M-YOLOv4 algorithm significantly improves the learning ability of the network model, making the average regression rate reach 91.35%, which can efficiently detect the status of passing ships. This study not only improves the intelligence level of hydropower equipment, but also provides an efficient and environmentally friendly solution for waterway monitoring. By combining clean energy and advanced target detection technology, this paper provides an important theoretical basis and practical reference for the sustainable development of future water conservancy projects.


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    Titel :

    Research on Intelligent Beacon Device Based on Bucket Hydropower and YOLO Algorithm


    Beteiligte:
    Gong, Xinyu (Autor:in) / Wu, Shixian (Autor:in)


    Erscheinungsdatum :

    23.10.2024


    Format / Umfang :

    1019965 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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