兵工自动化2026，Vol.45Issue(3)：39-43,5.DOI:10.7690/bgzdh.2026.03.007
基于改进YOLOv8的轻量化螺栓检测算法
Lightweight Bolt Detection Algorithm Based on Improved YOLOv8
摘要
Abstract
Aiming at the problem that the bolt target detection algorithm for steel frame is difficult to deploy due to the large amount of calculation,and the detection accuracy is not high due to the dense distribution of bolts in the construction scene,a lightweight bolt detection algorithm based on improved YOLOv8 is proposed.The ScConv module is used to fuse the C2f module in the feature extraction network,and the SRU and CUR in the module are used to reduce the space and channel redundancy of the network,so as to lighten the model;The P2 small target detection layer is introduced into the neck structure,and the BiFPN network structure is fused to increase the two-way connection path,which promotes the feature propagation up and down,and improves the accuracy of the network for bolt detection.The experimental results show that the proposed algorithm performs well in the self-collected data set,and the mAP accuracy is improved by 9.9%compared with the original network,while the number of model parameters and the model size are reduced by 0.973×106 and 1.7 MB respectively.关键词
目标检测/YOLOv8/BiFPN/ScConvKey words
object detection/YOLOv8/BiFPN/ScConv分类
信息技术与安全科学引用本文复制引用
骆清心,花国祥,闫纪源,史宇航,潘莫寂..基于改进YOLOv8的轻量化螺栓检测算法[J].兵工自动化,2026,45(3):39-43,5.基金项目
江苏省基础研究计划自然科学基金-青年基金项目(BK20230173) （BK20230173）
