[1]李 佳 杨建波 潘慧晓 赵卜兴 姜玉亭.基于机器视觉的装配构件吊装辅助技术研究[J].大众科技,2023,25(5):8-12.
 Research on Auxiliary Technology of Assembly Component Hoisting Based on Machine Vision[J].Popular Science & Technology,2023,25(5):8-12.
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基于机器视觉的装配构件吊装辅助技术研究()
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《大众科技》[ISSN:1008-1151/CN:45-1235/N]

卷:
25
期数:
2023年5
页码:
8-12
栏目:
信息技术与通信
出版日期:
2023-05-20

文章信息/Info

Title:
Research on Auxiliary Technology of Assembly Component Hoisting Based on Machine Vision
作者:
李 佳 杨建波 潘慧晓 赵卜兴 姜玉亭
(桂林电子科技大学建筑与交通工程学院,广西 桂林 541004)
关键词:
机器视觉装配式建筑装配构件
Keywords:
machine vision prefabricated buildings assembly components
文献标志码:
A
摘要:
在装配式建筑的构件吊装施工过程中,存在地面人员与塔吊操作人员产生视觉信息差、工人在构件装配操作过程中有较高危险性等问题。文章利用二维码存储装配构件的信息,运用机器视觉识别二维码,结合坐标系转换,实现装配构件安装位置识别;对摄像头获取图像进行RGB到HSV颜色空间转换,使用颜色分割算法,得到二值化图像,再进行形态学运算滤波处理,通过图像轮廓搜寻实现装配构件实时位姿识别。将建筑构件安装位置和实时位姿进行识别结果作为吊装过程操控指导信息,通过操控系统搭载的机械臂,并与塔吊协同,可完成建筑装配构件的辅助安装操作。
Abstract:
In the process of component hoisting construction of prefabricated buildings, there are some problems such as poor visual information between ground personnel and tower crane operators, and high risk of workers in the process of component assembly operation. In this paper, the two-dimensional code is used to store the information of assembly components, and the machine vision is used to identify the two-dimensional code, and the coordinate system transformation is used to realize the installation position identification of assembly components; The RGB to HSV color space conversion is carried out for the image acquired by the camera, and the binary image is obtained by using the color segmentation algorithm. Then the morphological operation and filtering processing are carried out, and the real-time pose recognition of assembly components is realized through the image contour search. The identification results of the installation position and real-time posture of the building components are used as the guidance information for the hoisting process. The auxiliary installation operation of the building assembly components can be completed by manipulating the mechanical arm carried by the system and cooperating with the tower crane.

参考文献/References:

[1] 房霆宸,左俊卿,龚剑. 计算机视觉在建筑工程施工领域的研究与应用[J]. 建筑施工,2021,43(11): 2376-2379,2382.[2] 王炎. 计算机视觉信息处理技术在建筑结构中的影像识别模式研究[J]. 粘接,2021,45(1): 78-80.[3] 段茵. 基于QR二维码的识别技术研究与实现[D]. 西安: 西安理工大学,2018.[4] 刘泽. 基于深度学习和OpenCV的自动泊车车位视觉检测与定位系统设计[D]. 镇江: 江苏大学,2019.[5] CHEMOV V, ALANDER J, BOCHKO V. Integer-based accurate conversion between RGB and HSV color spaces[J]. Computers and Electrical Engineering, 2015, 46: 328-337.[6] 张成斌. 形态与形态小波降噪技术及其在位移测量中的应用[D]. 南京: 南京航空航天大学,2016.

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备注/Memo

备注/Memo:
【收稿日期】2022-11-07【基金项目】广西科技重大专项项目“应急救援机器人技术研发与成果转化”(2022AA05002);国家大学生创新训练项目“装配式建筑构件吊装智能辅助装备研发”。【作者简介】李佳(1999-),男,广西玉林人,桂林电子科技大学建筑与交通工程学院学生,研究方向为建筑智能化技术。【通信作者】杨建波(1976-),男,江西玉山人,桂林电子科技大学建筑与交通工程学院高级工程师(聘副教授),硕士,研究方向为建筑智能装备技术。
更新日期/Last Update: 2023-07-17