Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM

预制混凝土 质量保证 工程类 激光扫描 比例(比率) 计算机科学 建筑工程 结构工程 激光器 运营管理 量子力学 光学 物理 外部质量评估
作者
Minkoo Kim,Qian Wang,Joon-Woo Park,Jack C.P. Cheng,Hoon Sohn,C. C. Chang
出处
期刊:Automation in Construction [Elsevier BV]
卷期号:72: 102-114 被引量:204
标识
DOI:10.1016/j.autcon.2016.08.035
摘要

This study presents a quality inspection technique for full-scale precast concrete elements using laser scanning and building information modeling (BIM). In today's construction industry, there is an increasing demand for modularization of prefabricated components and control of their dimensional quality during the fabrication and assembly stages. To meet these needs, this study develops a non-contact dimensional quality assurance (DQA) technique that automatically and precisely assesses the key quality criteria of full-scale precast concrete elements. First, a new coordinate transformation algorithm is developed taking into account the scales and complexities of real precast slabs so that the DQA technique can be fully automated. Second, a geometry matching method based on the Principal Component Analysis (PCA), which relates the as-built model constructed from the point cloud data to the corresponding as-designed BIM model, is utilized for precise dimension estimations of the actual precast slab. Third, an edge and corner extraction algorithm is advanced to tackle issues encountered in unexpected conditions, i.e. large incident angles and external steel bars being located near the edge of precast concrete elements. Lastly, a BIM-assisted storage and delivery approach for the obtained DQA data is proposed so that all relevant project stakeholders can share and update DQA data through the manufacture and assembly stages of the project. The applicability of the proposed DQA technique is validated through field tests on two full-scale precast slabs, and the associated implementation issues are discussed. Field test results reveal that the proposed DQA technique can achieve a measurement accuracy of around 3.0 mm for dimension and position estimations.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
超勍发布了新的文献求助10
1秒前
小马甲应助yuanshl1985采纳,获得10
1秒前
zhuxiaonian完成签到,获得积分10
4秒前
田様应助淘气科研采纳,获得10
4秒前
chenyi完成签到,获得积分10
5秒前
zyyyy完成签到,获得积分10
5秒前
奶黄包完成签到 ,获得积分10
5秒前
SYLH应助海阔天空采纳,获得10
5秒前
5秒前
机灵又蓝完成签到,获得积分10
6秒前
张土豆完成签到 ,获得积分10
6秒前
善学以致用应助小王采纳,获得10
6秒前
orang完成签到,获得积分10
7秒前
巧巧艾完成签到,获得积分10
7秒前
8秒前
邵洋完成签到,获得积分10
8秒前
sl发布了新的文献求助10
8秒前
9秒前
小迪迦奥特曼完成签到,获得积分10
9秒前
9秒前
cckk发布了新的文献求助10
10秒前
夏目由美完成签到 ,获得积分10
10秒前
Jasper应助哦哦哦采纳,获得10
11秒前
YYD完成签到,获得积分10
11秒前
超勍完成签到,获得积分10
11秒前
碧蓝碧凡发布了新的文献求助10
12秒前
Popeye应助鹤鸣采纳,获得30
12秒前
YYD发布了新的文献求助10
13秒前
yuanshl1985发布了新的文献求助10
13秒前
积极的黑猫完成签到,获得积分10
14秒前
GB完成签到 ,获得积分10
14秒前
Metx完成签到 ,获得积分10
15秒前
孤独的涔完成签到,获得积分10
16秒前
Jay完成签到,获得积分10
16秒前
17秒前
深情安青应助hf采纳,获得10
19秒前
学不懂数学应助大观天下采纳,获得10
19秒前
醉熏的水绿完成签到 ,获得积分10
19秒前
秦艺完成签到,获得积分10
20秒前
20秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
Research on Disturbance Rejection Control Algorithm for Aerial Operation Robots 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038426
求助须知:如何正确求助?哪些是违规求助? 3576119
关于积分的说明 11374556
捐赠科研通 3305834
什么是DOI,文献DOI怎么找? 1819339
邀请新用户注册赠送积分活动 892678
科研通“疑难数据库(出版商)”最低求助积分说明 815029