Research on Transmission Line Foreign Object Detection Based on Edge Calculation
Yongbo Zhang, Xiangfeng Gong, Jian Sun, Youshui Tao, Wei Su · 2022
Transmission line foreign object detection plays an important role in improving the security, reliability and stability of transmission system. It's a challenge that transmission line foreign object detection achieves real-time on edge calculation as well as high performance. This paper proposes an object detector with both speed and accuracy based on YOLOv5, named YOLOv5-GHK. First, replacing Convolution, Ghost module has less parameters and calculation to achieve real-time speed. Then, network prediction with high-resolution feature improves accuracy of small transmission line foreign objects. Last, knowledge distillation ensures that lightweight model has less loss of precision. As a consequence, the proposed method runs at 36 FPS on NPU with a state-of-the-art accuracy.