院报 ›› 2024, Vol. 41 ›› Issue (1): 196-202.DOI: 10.11988/ckyyb.20221106

• 水利信息化 • 上一篇    

一种大体积混凝土自动化通水温控方法

王明涛1, 周骅1, 赵麒2   

  1. 1.贵州大学 大数据与信息工程学院,贵阳 550025;
    2.贵州民族大学 机械与电子工程学院,贵阳 550025
  • 收稿日期:2022-08-29 修回日期:2022-12-03 出版日期:2024-01-01 发布日期:2024-01-15
  • 通讯作者: 周骅(1978-),男,贵州贵阳人,副教授,博士,主要研究物联网、电路系统。E-mail:zhouhua97@gmail.com
  • 作者简介:王明涛(1997-),男,贵州遵义人,硕士,主要研究嵌入式与控制系统。E-mail:wangming6d9b@foxmail.com
  • 基金资助:
    国家自然科学基金项目(U1836205);国家重点研发计划项目(2021YFB3101100);贵阳市科技计划项目([2021]1-5号)

A Method of Automated Water Temperature Control for Large Volume Concrete

WANG Ming-tao1, ZHOU Hua1, ZHAO Qi2   

  1. 1. College of Big Data and Information Engineering, Guizhou University, Guiyang 550025, China;
    2. College of Mechanical Electronical and Engineering, Guizhou Minzu University,Guiyang 550025, China
  • Received:2022-08-29 Revised:2022-12-03 Online:2024-01-01 Published:2024-01-15

摘要: 为了实现施工期大体积混凝土通水温控的自动化,根据《大体积混凝土温度测控技术规范》(GB/T 51028—2015),创新性地设计了一种基于自适应级联模糊控制算法的工业控制平台。硬件平台由控制柜、混水装置、温度采集网络组成,分别完成计算、执行、采集的工作;首次将自适应模糊控制应用到大体积混凝土温度控制中,将混凝土里表温差、温度变化率、进水温度3个关键参数综合考虑、复合计算,进行两级模糊推理,然后将推理结果作用到2个流量阀门,分别控制回水与冷水的混合比,得到满足温度标准的混合水,压入提前铺设好的混凝土冷却管道中,以此实时控制混凝土温度。通过建模仿真与工程实践验证了该控制策略能保持混凝土内部温度与进水温度差<25 ℃,在此基础上抑制混凝土温升,仿真的混凝土降温速度为1.69 ℃/d,实际工程应用的混凝土降温速度分别为1.59、1.56 ℃/d,均低于上限警告阈值2 ℃/d;仿真与实际工程数据均验证了该控制平台的有效性。

关键词: 大体积混凝土, 自动化, 通水温控, 模糊控制, 混凝土温控仿真

Abstract: To automatically control the water temperature of mass concrete during construction, we designed an innovative industrial control platform using the self-adaptive cascade fuzzy control algorithm based on the Technical Specification for Temperature Measurement and Control of Bulk Concrete (GB/T 51028-2015). The hardware platform includes a control cabinet, water mixing device, and temperature collection network, which perform the calculation, execution, and collection tasks respectively. For the first time, the self-adaptive fuzzy control is applied to the temperature control of mass concrete. It integrates and combines three key parameters, namely, the temperature difference between concrete lining and surface, temperature change rate, and inlet water temperature, for two-level fuzzy reasoning. The reasoning results are then utilized to control the mixing ratio of return water and cold water through two flow valves. This ensures the production of mixed water that meets the temperature standard, which is then pressed into the pre-laid cooling pipes to regulate the concrete temperature in real-time. Modeling simulation and engineering practice have validated that this control strategy maintains the temperature difference between the internal concrete temperature and the inlet water temperature below 25 ℃, effectively suppressing the temperature rise of the concrete. The simulation shows a concrete cooling rate of 1.69 ℃/day, while in actual engineering application, the cooling rates recorded are 1.59 and 1.56 ℃/day, which are below the upper warning threshold of 2 ℃/day. Consequently, both the simulation results and the data from actual engineering support the effectiveness of this control platform.

Key words: mass concrete, automation, water temperature control, fuzzy control, simulation of concrete temperature control

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