首页|基于机器视觉的预制叠合板智能检测关键技术

基于机器视觉的预制叠合板智能检测关键技术

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装配式建筑采用工业化生产、装配化施工,具有施工效率高、节能环保等特点,受到国家的大力扶持,而预制叠合板作为预制率、装配率高的预制构件,其质量优劣关系整个工程.预制叠合板在生产过程中存在一些问题,如混凝土浇筑前的隐蔽验收工作采用人工检查方法,人工投入量大,质量检测水平和效率低,容易漏检、错检,严重制约了混凝土叠合板生产效率.以预制叠合板为研究对象,开展图像畸变校正算法与数据增强算法研究,研究改进YOLOv7预制叠合板精准识别算法、钢筋排布和间距识别方法,开发了一套基于机器视觉的预制叠合板智能检测控制系统.系统可对叠合板尺寸误差、预埋件位置及数量进行智能评估,从而减少质检人员投入,提高生产效率和产品合格率.
Key Technology of Intelligent Detection for Precast Composite Panels Based on Machine Vision
Prefabricated buildings adopt industrial production and prefabricated construction,which have the characteristics of high construction efficiency,energy conservation and environmental protection,and receive strong support from the country.As precast components with very high precast and assembly rates,the quality of precast composite panels is related to the entire project.There are some problems in the production process of precast composite panels,such as the use of manual inspection for concealed acceptance work before concrete pouring,which results in a large amount of manual input,low quality detection level and efficiency,and easy omission and misinspection,seriously restricting the production efficiency of concrete composite panels.The precast composite panels are taken as the research object,the research on image distortion correction algorithm and data enhancement algorithm is conducted,improving YOLOv7 precast composite panel precise recognition algorithm and steel bar layout and spacing recognition method are researched,and a machine vision based intelligent detection and control system for precast composite panels is developed.The system can intelligently evaluate the size error,embedded part position and quantity of composite panels,thereby reducing the investment of quality inspectors,improving production efficiency and product qualification rate.

informationprecast composite panelsmachine visionimage processingdetection

于海洋、李海生、彭伟、孙宏伟、于晓光

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荣华建设集团有限公司,山东 青岛 266000

荣华(青岛)建设科技有限公司,山东 青岛 266000

山东建筑大学,山东 济南 250000

信息化 预制叠合板 机器视觉 图像处理 检测

2024

施工技术(中英文)
亚太建设科技信息研究院 中国建筑设计研究院 中国建筑工程总公司 中国土木工程学会

施工技术(中英文)

影响因子:1.244
ISSN:2097-0897
年,卷(期):2024.53(20)