基于YOLOv5的施工振动邻近区域房屋裂缝智能检测
Intelligent Detection of House Cracks in the Vicinity of Construction Vibrations Based on YOLOv5
戴保华1
作者信息
- 1. 安徽建工检测科技集团有限公司,安徽 合肥 230031
- 折叠
摘要
施工振动可能导致邻近区域的房屋产生裂缝,传统的裂缝检测技术由于现场环境和裂缝形态等因素影响检测效率,为此将智能检测技术运用于房屋裂缝检测中.采用YOLOv5 算法,构建包含 3 917 张图片的混凝土裂缝数据集,经过 1 000 个训练轮次后,模型精度和召回率均达到较高水平,同时损失函数减小至极小值,表明该模型用于裂缝检测的精确性.将训练的模型用于 38 所房屋的裂缝检测中,检测效果良好.
Abstract
Construction vibration may cause cracks in adjacent buildings.Traditional crack detection techniques are affected by factors such as on-site environment and crack morphology,which affect detection efficiency.Therefore,intelligent detection technology is applied to crack detection in buildings.The YOLOv5 algorithm is adopted,and a concrete crack dataset containing 3 917 images is constructed.After 1 000 training epochs,the model achieves high precision and recall rates,while the loss function decreases to a small value,indicating the accuracy of the model for crack detection.The trained model is applied to crack detection in 38 houses in practical engineering projects,showing good detection performance.
关键词
施工振动/YOLOv5/智能检测/房屋裂缝Key words
construction vibrations/YOLOv5/intelligent detection/house cracks引用本文复制引用
出版年
2024
NETL
NSTL
万方数据