{"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}
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.
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
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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.