基于数字孪生技术的钢结构施工质量控制方法

Digital Twin Pub Date : 2023-05-10 DOI:10.12688/digitaltwin.17824.1

Zhansheng Liu, Lejia Wu, Zisheng Liu, Yanchi Mo

{"title":"基于数字孪生技术的钢结构施工质量控制方法","authors":"Zhansheng Liu, Lejia Wu, Zisheng Liu, Yanchi Mo","doi":"10.12688/digitaltwin.17824.1","DOIUrl":null,"url":null,"abstract":"Background: The quality of construction is crucial in evaluating steel structure. However, traditional quality control methods for steel structure construction have been criticized for their lack of intelligence, resulting in a heavier reliance on manual experience and post-construction inspections to address quality issues. This shortcoming makes quality management inefficient and labor-intensive. To address this issue, this paper proposes a smart quality control method based on digital twin technology. Methods: In this framework, data collection is used for subsequent quality control throughout the construction process. To improve pre-construction quality control, a mixed reality (MR) system is used to guide and train personnel. During the steel structure construction process, the Markov method is used to analyze and predict real-time data. Results: To test the effectiveness of the proposed method, ten sets of parallel tests were conducted to predict whether the bolt torque value was normal or not, resulting in an 80% accuracy rate. Conclusions: The proposed method for steel structure construction quality control was effectively certified, achieving active prevention and real-time control of quality problems and improving the overall intelligence level of quality control.","PeriodicalId":29831,"journal":{"name":"Digital Twin","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Quality control method of steel structure construction based on digital twin technology\",\"authors\":\"Zhansheng Liu, Lejia Wu, Zisheng Liu, Yanchi Mo\",\"doi\":\"10.12688/digitaltwin.17824.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: The quality of construction is crucial in evaluating steel structure. However, traditional quality control methods for steel structure construction have been criticized for their lack of intelligence, resulting in a heavier reliance on manual experience and post-construction inspections to address quality issues. This shortcoming makes quality management inefficient and labor-intensive. To address this issue, this paper proposes a smart quality control method based on digital twin technology. Methods: In this framework, data collection is used for subsequent quality control throughout the construction process. To improve pre-construction quality control, a mixed reality (MR) system is used to guide and train personnel. During the steel structure construction process, the Markov method is used to analyze and predict real-time data. Results: To test the effectiveness of the proposed method, ten sets of parallel tests were conducted to predict whether the bolt torque value was normal or not, resulting in an 80% accuracy rate. Conclusions: The proposed method for steel structure construction quality control was effectively certified, achieving active prevention and real-time control of quality problems and improving the overall intelligence level of quality control.\",\"PeriodicalId\":29831,\"journal\":{\"name\":\"Digital Twin\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digital Twin\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12688/digitaltwin.17824.1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Twin","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12688/digitaltwin.17824.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

背景：在评估钢结构时，施工质量至关重要。然而，钢结构施工的传统质量控制方法因缺乏智能性而受到批评，导致更严重地依赖人工经验和施工后检查来解决质量问题。这一缺点使得质量管理效率低下，劳动密集。针对这一问题，本文提出了一种基于数字孪生技术的智能质量控制方法。方法：在该框架中，数据收集用于整个施工过程的后续质量控制。为了改进施工前的质量控制，使用混合现实（MR）系统来指导和培训人员。在钢结构施工过程中，采用马尔可夫方法对实时数据进行分析和预测。结果：为了测试所提出方法的有效性，进行了十组平行测试来预测螺栓扭矩值是否正常，准确率为80%。结论：所提出的钢结构施工质量控制方法得到了有效验证，实现了对质量问题的主动预防和实时控制，提高了质量控制的整体智能化水平。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Quality control method of steel structure construction based on digital twin technology

Background: The quality of construction is crucial in evaluating steel structure. However, traditional quality control methods for steel structure construction have been criticized for their lack of intelligence, resulting in a heavier reliance on manual experience and post-construction inspections to address quality issues. This shortcoming makes quality management inefficient and labor-intensive. To address this issue, this paper proposes a smart quality control method based on digital twin technology. Methods: In this framework, data collection is used for subsequent quality control throughout the construction process. To improve pre-construction quality control, a mixed reality (MR) system is used to guide and train personnel. During the steel structure construction process, the Markov method is used to analyze and predict real-time data. Results: To test the effectiveness of the proposed method, ten sets of parallel tests were conducted to predict whether the bolt torque value was normal or not, resulting in an 80% accuracy rate. Conclusions: The proposed method for steel structure construction quality control was effectively certified, achieving active prevention and real-time control of quality problems and improving the overall intelligence level of quality control.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Digital Twin digital twin technologies-

自引率

0.00%

发文量

期刊介绍： Digital Twin is a rapid multidisciplinary open access publishing platform for state-of-the-art, basic, scientific and applied research on digital twin technologies. Digital Twin covers all areas related digital twin technologies, including broad fields such as smart manufacturing, civil and industrial engineering, healthcare, agriculture, and many others. The platform is open to submissions from researchers, practitioners and experts, and all articles will benefit from open peer review.  The aim of Digital Twin is to advance the state-of-the-art in digital twin research and encourage innovation by highlighting efficient, robust and sustainable multidisciplinary applications across a variety of fields. Challenges can be addressed using theoretical, methodological, and technological approaches. The scope of Digital Twin includes, but is not limited to, the following areas:  ● Digital twin concepts, architecture, and frameworks ● Digital twin theory and method ● Digital twin key technologies and tools ● Digital twin applications and case studies ● Digital twin implementation ● Digital twin services ● Digital twin security ● Digital twin standards Digital twin also focuses on applications within and across broad sectors including: ● Smart manufacturing ● Aviation and aerospace ● Smart cities and construction ● Healthcare and medicine ● Robotics ● Shipping, vehicles and railways ● Industrial engineering and engineering management ● Agriculture ● Mining ● Power, energy and environment Digital Twin features a range of article types including research articles, case studies, method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.