河北科技大学学报2025，Vol.46Issue(5)：542-552,11.DOI:10.7535/hbkd.2025yx05007
基于改进EB-YOLO-v8n的耗能梁损伤识别
Damage identification of link beam based on improved EB-YOLO-v8n
摘要
Abstract
To accurately and quickly evaluate the damage state of link beams after the earthquake,the EB-YOLO-v8n link beam damage identification model was proposed by adding an efficient muti-scale attention module(EMA)and a bidirectional feature pyramid network module structure(BiFPN)to the YOLO-v8n model.Firstly,quasi-static tests of 9 link beams with different parameters were designed and completed.The local damage of the structure under different damage states was recorded and summarized into a dataset.Secondly,Mosaic+Fliplr data enhancement technology was used to enhance the input data to ensure the quality,and a total of 2 612 images were obtained as the dataset.Then,the various damages in the dataset were labeled and input into the model for training.Finally,the effectiveness of each improved module was analyzed through ablation experiments.The results show that the average accuracy of the EB-YOLO-v8 model is higher than that of the other models in this paper.This means the improved model has stronger robustness with basically unchanged parameter quantities.Besides,according to the results of the ablation experiment,the average accuracy of the EB-YOLO-v8n model is 1.2%and 3.8%higher than that of E-YOLO-v8n(introducing an efficient multi-scale attention module)and B-YOLO-v8n(replacing the path aggregation network in the feature pyramid networks(FPN)with a weighted BiFPN),respectively,and it also has a certain advantage in the average recognition time per image.In general,the EB-YOLO-v8n model balances accuracy and speed,fitting the high-precision and speed requirements for post-earthquake damage recognition,which can meet the needs in complex engineering conditions.关键词
结构设计/耗能梁/目标检测/损伤识别/YOLO-v8nKey words
structure design/link beam/target detection/damage identification/YOLO-v8n分类
土木建筑引用本文复制引用
于海丰,曹坤,苏佶智,张辉杰,方斌,王奇智,位翠霞,岳宏亮..基于改进EB-YOLO-v8n的耗能梁损伤识别[J].河北科技大学学报,2025,46(5):542-552,11.基金项目
河北省自然科学基金(E2025208016,E2023208069,E2023208080) （E2025208016,E2023208069,E2023208080）
中央引导地方科技发展资金项目(236Z5408G) （236Z5408G）
河北省教育厅产学研合作专项(CXY2024045) （CXY2024045）
