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清华大学学报(自然科学版)  2022, Vol. 62 Issue (8): 1270-1280    DOI: 10.16511/j.cnki.qhdxxb.2022.25.037
  智能施工 本期目录 | 过刊浏览 | 高级检索 |
自密实混凝土全过程智能生产研究进展
吕淼1, 安雪晖1, 李鹏飞2, 张京斌3, 白皓1
1. 清华大学 水沙科学与水利水电工程国家重点实验室, 北京 100084;
2. 重庆交通大学 河海学院, 重庆 400074;
3. 河海大学 土木与交通学院, 南京 210098
Review of smart production techniques for the entire self-compacting concrete production process
LÜ Miao1, AN Xuehui1, LI Pengfei2, ZHANG Jingbin3, BAI Hao1
1. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China;
2. School of Hehai, Chongqing Jiaotong University, Chongqing 400074, China;
3. College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China
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摘要 自密实混凝土具有无需振捣便可通过自重填充模板的良好工作性能,但工作性能对原材料特性的变化具有高敏感度。现有自密实混凝土生产质量管理难度较高,生产环节与质量检测环节较为分散,导致原材料数据不准确,生产数据检测效率低。随着图像处理与人工智能技术的成熟,智能化与智慧化技术逐渐应用于包括原材料检测、配合比设计、搅拌生产和流变性能检测在内的生产全过程,原材料智能检测技术可辅助原材料质量管理,配合比智慧设计方法可用以应对原材料性能的波动、高效准确地确定配合比,基于搅拌状态的实时监测可实现搅拌过程中的配合比智慧调整,流变性能智能检测技术可以实时地通过非接触式方法获得不同尺度拌和物的流变性能。该文详细介绍了自密实混凝土全过程智能化生产技术的研究进展与成果,并指出目前研究的不足,展望未来发展趋势。
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关键词 自密实混凝土全过程智能生产配合比智慧设计智能检测配合比智慧调整    
Abstract:Self-compacting concrete (SCC) has good fluidity that can fill the voids without vibrations, but the concrete performance is very sensitive to material property changes. Existing SCC production methods have material quality management problems with production discontinuities leading to inaccurate material information and poor test results. New image recognition and artificial intelligence methods are enabling intelligent systems for the entire production process, including material property tests, mix design, and mixing production, and rheological property tests. Smart material property tests improve material quality management. The mix proportions can be accurately determined by intelligent mix design methods that cope with material property changes. Real-time monitoring of the mixing can optimize mix proportions during mixing. Smart rheological property tests can monitor the rheological properties of the self-compacting mixtures during mixing. This paper reviews the research on smart production for the entire SCC production process and summarizes current problems and future development prospects.
Key wordsself-compacting concrete (SCC)    smart production processes    intelligent mix designs    smart tests    intelligent mix adjustment
收稿日期: 2021-10-28      出版日期: 2022-03-31
基金资助:国家自然科学基金项目(52109153);江苏省博士后科研资助计划项目(2021K055A);中央高校基本科研业务费专项资金项目(B210201012)
通讯作者: 安雪晖,教授,E-mail:anxue@tsinghua.edu.cn      E-mail: anxue@tsinghua.edu.cn
作者简介: 吕淼(1992—),女,博士研究生。
引用本文:   
吕淼, 安雪晖, 李鹏飞, 张京斌, 白皓. 自密实混凝土全过程智能生产研究进展[J]. 清华大学学报(自然科学版), 2022, 62(8): 1270-1280.
LÜ Miao, AN Xuehui, LI Pengfei, ZHANG Jingbin, BAI Hao. Review of smart production techniques for the entire self-compacting concrete production process. Journal of Tsinghua University(Science and Technology), 2022, 62(8): 1270-1280.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2022.25.037  或          http://jst.tsinghuajournals.com/CN/Y2022/V62/I8/1270
  
  
  
  
  
  
  
  
  
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