摘要
预制构件叠合面的粗糙度是保证叠合构件新老混凝土共同工作的关键,相关规范虽规定了叠合面粗糙度限值,但未给出具体检测方法。目前常用的灌砂法、测深尺法、数字图像法和三维激光扫描法,存在成本高、精度低或设备昂贵等缺点,实际工程往往仅凭“目测”评估,与智能建造的行业发展趋势不符。研究提出了一种基于机器视觉的粗糙度检测方法,首先使用深度相机获取叠合面点云图,然后通过分割点云获得基准面方程,最后计算出检测区域粗糙度值。进一步开发了便携式粗糙度检测装置,应用于工程检测。与测深尺法的检测结果对比表明:机器视觉检测方法精度和效率均高,所建议的基准面计算方法可行,开发的检测装置可直接服务于预制构件质量的智能管控。
The roughness of the laminated surface plays a crucial role in ensuring good connection performance between new and existing concrete.Although standards have made clear requirements for the roughness value,a specific detection method has yet to be provided.At present,common roughness detection methods such as sand filling,bathymetric,digital image and three-dimensional laser scanning are plagued by issues including high costs,low accuracy,which is inconsistent with the development of the intelligent construction.This paper proposes a machine vision inspection method for roughness detection of the laminated surface.Firstly,use a depth camera to capture the point cloud on the laminated surface.Subsequently,segment the point cloud and calculate the datum equation.Following the calculation,the roughness value is determined.Based on this method,a portable and intelligent roughness detection device is developed,and tests are carried out on practical engineering.Compared with the bathymetric ruler method,the results show that the detection method has high accuracy and efficiency.The proposed datum surface computation method is feasible.Furthermore,the developed detection device can be directly applied in the intelligent management of the quality of prefabricated components.
作者
陈隽
范泽楷
梅长周
王卓琳
CHEN Jun;FAN Zekai;MEI Changzhou;WANG Zhuolin(College of Civil Engineering,Tongji University,Shanghai 200092,China;Shanghai Research Institute of Building Science,Shanghai 200032,China)
出处
《土木工程与管理学报》
2025年第1期59-65,80,共8页
Journal of Civil Engineering and Management
基金
国家自然科学基金联合基金重点项目(U1711264)。
关键词
智能建造
叠合面
粗糙度
基准面
机器视觉
intelligent construction
laminated surface
roughness
datum surface
machine vision
