Deep Learning-Based Unmanned Aerial Vehicle Integrated Inspection System for Power Transmission Transformation and Distribution
This paper proposes a deep learning-based integrated inspection system for unmanned aerial vehicles(UAV)in power transmission,transformation,and distribution.The system utilizes advanced computer vision algorithms and an enhanced YOLOv5 network for the precise identification and positioning of defects in power transmission and distribution equipment.By establishing a large-scale defect dataset and optimizing the algorithm,the system significantly improves the accuracy and reliability of defect detection.Additionally,the system integrates modules such as an onboard computing platform and ground monitoring software,enabling real-time processing of inspection data and remote monitoring.
deep learningunmanned aerial vehicleinspection systemtransmissiontransformation and distribution equipment
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