辽宁工程技术大学学报（自然科学版）2025，Vol.44Issue(5)：590-596,7.DOI:10.11956/j.issn.1008-0562.20250135
基于改进YOLOv8的混凝土裂缝检测算法
Concrete crack detection algorithm based on improved YOLOv8
摘要
Abstract
In order to realize the accurate and efficient detection of concrete cracks,a concrete crack detection model YOLO-CCD based on YOLOv8 s is proposed.The multi-scale convolution module PSConv(poly-scale convolution)is introduced to enhance the learning ability of cross-scale features and improve the detection effect of small cracks and cracks in complex backgrounds.The efficient channel attention(ECA)mechanism is used to enhance the dependence between feature channels and optimize feature representation.The SIoU loss function is introduced to optimize the bounding box regression process by comprehensively considering the geometric features,so as to improve the detection accuracy of the model.Compared with the YOLOv8 s model,the average accuracy mAP50 and mAP50-95 of the improved model are increased by 7.9%and 2.4%,respectively.Compared with other detection methods,the model proposed in this paper has significant advantages in detection accuracy and computational efficiency.The research conclusion provides a new feasible method for concrete crack detection.关键词
目标检测/YOLOv8/混凝土裂缝/混凝土裂缝检测/高效通道注意力/多尺度卷积/损失函数Key words
object detection/YOLOv8/concrete crack/concrete crack detection/efficient channel attention/poly-scale convolution/loss function分类
建筑与水利引用本文复制引用
赵文华,刘澳鹏,杜常博,孙琦,孔佳慧..基于改进YOLOv8的混凝土裂缝检测算法[J].辽宁工程技术大学学报（自然科学版）,2025,44(5):590-596,7.基金项目
国家自然科学基金项目(52074144) （52074144）
辽宁省自然科学基金项目(2019-MS-158) （2019-MS-158）
辽宁省教育厅科学研究基金项目(LJ2020JCL001) （LJ2020JCL001）
