基于负压吸附爬壁机器人和Transformer的混凝土桥塔裂缝识别检测
Recognition and Detection of Concrete Bridge Tower Cracks Using a Negative Pressure Adhesion Wall-climbing Robot and Transformer
丁威 1夏哲 1舒江鹏 1叶建龙 2项贻强1
作者信息
- 1. 浙江大学建筑工程学院,浙江杭州 310058
- 2. 浙江省交通集团检测科技有限公司,浙江杭州 310058
- 折叠
摘要
为了解决大型桥梁混凝土桥塔结构裂缝难以高效、安全、精准量化识别的问题,提出了基于爬壁机器人和Transformer的桥塔裂缝识别检测方法.该方法以基于负压吸附机制的爬壁机器人为装备载体,其可在混凝土桥塔上快速移动并近距离采集表观病害高清数据.通过建立包含图像拼接、特征金字塔Transformer(Feature Pyramid Transformer,FPT)裂缝分割网络、尺度量化计算的裂缝识别方法,得到裂缝关键位置的宽度数据,并输出裂缝全局分布可视化结果,有效提升了微小裂缝的分割和边缘定位精度.基于试验验证了该方法的可行性与识别检测精度,并成功将其应用于中国东部某跨海大桥主塔裂缝检测工程.检测结果表明:该法对实际桥塔表面分布在0.1～3.3 mm宽度范围内的多尺度裂缝进行检测,宽度量化的最大误差小于10％.研究成果具有较好的应用前景,有望进一步推进现有混凝土桥梁结构检测技术与装备的智能化发展.
Abstract
To achieve efficient,safe,and accurate quantitative identification of cracks in concrete towers of large bridges,this study proposes a crack recognition and detection method for bridge towers based on wall-climbing robots and transformers.This method uses a wall-climbing robot based on the negative-pressure adhesion mechanism as the equipment carrier to move quickly on a concrete bridge tower and collect high-resolution data from apparent diseases at close range.A crack quantification evaluation method,including image stitching,a Feature Pyramid Transformer(FPT)crack segmentation network,and quantitative dimension calculations,was established.The width data of the key positions of the crack were obtained,along with the visualization result of the global distribution of the crack.Additionally,the proposed method effectively improved the crack segmentation and boundary location accuracy of microcracks.The feasibility and recognition accuracy of the method were verified experimentally,and the method was successfully applied to the main tower crack detection project of a cross-sea bridge in Eastern China.The multi-scale cracks distributed in the width range of 0.1-3.3 mm on the bridge tower surface were detected,and the maximum error of width quantification was less than 10％.The results of this study have good application prospects and are expected to promote the intelligent development of existing concrete bridge structure detection technologies and equipment.
关键词
桥梁工程/桥塔裂缝检测/爬壁机器人/特征金字塔Transformer/多尺度裂缝Key words
bridge engineering/bridge tower crack detection/wall-climbing robot/Feature Pyra-mid Transformer/multi-scale cracks引用本文复制引用
基金项目
国家重点研发计划项目(2023YFE0115000)
浙江省领雁计划项目(2023C01161)
浙江省交通厅科技项目(202217)
出版年
2024
NETL
NSTL
万方数据