辽宁工程技术大学学报（自然科学版）2025，Vol.44Issue(1)：113-119,7.
基于改进YOLOv8模型的树线接地故障识别
Tree line grounding fault identification technology based on improved YOLOv8 model
摘要
Abstract
In order to improve the recognition effect of tree line grounding fault detection in power system,an improved YOLOv8 model is proposed.The model enhances the feature representation ability by inserting the SimAM attention mechanism,and uses the GIoU loss function to improve the accuracy of the bounding box prediction and improve the fault recognition performance of the model in complex environments.In order to verify the performance of the improved YOLOv8 model,the ablation experiment,the insertion position change experiment of the SimAM attention mechanism module,the loss function selection experiment,and the comparison experiment with other recognition models are carried out.The experimental results show that the improved YOLOv8 model has the highest recognition accuracy,recall rate and average accuracy.The model effectively improves the recognition accuracy of the tree-line grounding fault detection image and provides support for the intelligent operation and maintenance of transmission lines.关键词
电力系统/树线接地故障/YOLOv8模型/SimAM注意力机制/GIoU损失函数Key words
power system/tree line grounding fault/YOLOv8 model/SimAM attention mechanism/GIoU loss function分类
动力与电气工程引用本文复制引用
王洪江,刘金圣,赵宏,赵婷婷,代钦,高英才..基于改进YOLOv8模型的树线接地故障识别[J].辽宁工程技术大学学报（自然科学版）,2025,44(1):113-119,7.基金项目
辽宁省教育厅高校基本科研项目(JYTMS20230323 （）
LJ222411632019) （）
