数字孪生驱动的预应力拉索索力智能预测方法研究

刘占省; 史国梁; 王竞超

doi:10.13204/j.gyjzG20110502

数字孪生驱动的预应力拉索索力智能预测方法研究

doi: 10.13204/j.gyjzG20110502

北京工业大学城市建设学部, 北京 100124

基金项目:

国家重点研发计划科技冬奥专项（2018YFF0300300）。

详细信息

作者简介:
刘占省,男,1983年出生,工学博士,副教授,硕士生导师。电子信箱:lzs4216@163.com

计量
- 文章访问数: 338
- HTML全文浏览量: 13
- PDF下载量: 24
- 被引次数: 0
出版历程
- 收稿日期: 2020-11-05
- 网络出版日期: 2021-09-16
- 刊出日期: 2021-09-16

RESEARCH ON INTELLIGENT PREDICTION METHOD OF PRESTRESSED CABLE FORCE BASED ON DIGITAL TWINS

College of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China

摘要

摘要: 针对拉索张拉过程中索力预测精度和智能化程度低的问题，提出了数字孪生驱动的预应力拉索索力智能预测方法。根据对拉索张拉的研究现状，分析了影响拉索索力的主要因素，总结了当前预应力拉索索力预测的方法。在智能预测闭环控制的理论框架下，探索了数字孪生驱动的预测维护方法。在此基础上，搭建了基于数字孪生的融合型预测方法框架，并探索了融合型预测维护方法的实施流程，通过数据的融合由工况参数预测出拉索的索力。针对轮辐式索桁架进行案例分析，验证了该方法的有效性。由数字孪生驱动的预应力拉索索力智能预测方法可以由工况参数直接预测索力的状态，提高了预应力钢结构安全评估的精确性和智能化。
- 数字孪生 /
- 预应力拉索 /
- 索力预测 /
- 融合算法 /
- 安全评估
Abstract: Aiming at the problem of low accuracy and intelligence of cable force prediction in the cable tensioning process, an intelligent prediction method of prestressed cable force based on digital twins was proposed. According to the current research status of cable tension, the main factors affecting the cable force were analyzed, and the current method of prestressed cable force prediction were summarized. Under the theoretical framework of intelligent predictive closed-loop control, a predictive maintenance method based on digital twins was explored. On this basis, the framework of the fusion prediction method based on digital twins was established, and the implementation process of the fusion prediction and maintenance method was explored. The cable force was predicted from the working condition parameters through the fusion of data. A case analysis of the spoke-type cable truss verified the effectiveness of the method. The intelligent prediction method for prestressed cable force based on digital twins could directly predict the state of cable force from working condition parameters, which improve the accuracy and intelligence of the safety assessment of prestressed steel structures.
- digital twins /
- prestressed cable /
- cable force prediction /
- fusion algorithm /
- safety assessment

HTML全文

参考文献(27)

[1]	张爱林, 刘廷勇, 张艳霞, 等.基于智能建造的快速全装配大跨度预应力空间钢结构体系创新研究展望[J]. 北京工业大学学报, 2020, 46(6):591-603.
[2]	张谨, 杨律磊, 龚敏锋, 等.苏州现代传媒广场新型钢结构技术研究与应用[J]. 建筑结构, 2019, 49(1):25-35 , 48.
[3]	陈志华, 马青, 闫翔宇, 等.复合式索穹顶施工误差影响及控制技术研究[J]. 湖南大学学报(自然科学版), 2018, 45(9):47-56.
[4]	郭彦林, 张旭乔.温度作用和索长误差对采用定长索设计的张拉结构影响研究[J]. 土木工程学报, 2017, 50(6):11-22 , 61.
[5]	ZHU M L, DONG S L, YUAN X F. Failure Analysis of a Cable Dome Due to Cable Slack or Rupture[J]. Advances in Structural Engineering, 2013, 16(2):259-271.
[6]	张中昊, 支旭东, 李奇训, 等.新型索撑式单层球面网壳选型与预应力张拉模拟研究[J]. 工程力学, 2018, 35(10):193-202 , 211.
[7]	薛素铎, 王成林, 孙国军, 等.Levy型劲性支撑穹顶静力性能试验研究[J]. 建筑结构学报, 2020, 41(3):150-155.
[8]	THAI H T, KIM S E. Nonlinear Static and Dynamic Analysis of Cable Structures[J]. Finite Elements in Analysis & Design, 2011, 47(3):237-246.
[9]	ANDREW B, MOHAMMED H S, MOHAMED M.A BIM-Based Framework for Quantitative Assessment of Steel Structure Deconstructability[J]. Automation in Construction, 2019, 111.DOI: 10.1016/j.autcon.2019.103064.
[10]	ASHWEAR N, TAMADAPU G, ERIKSSON A. Optimization of Modular Tensegrity Structures for High Stiffness and Frequency Separation Requirements[J]. International Journal of Solids & Structures, 2015, 80:297-309.
[11]	AREZKI S, KAMEL L, AMAR K. Effects of Temperature Changes on the Behaviour of a Cable Truss System[J]. Journal of Constructional Steel Research, 2017, 129:111-118.
[12]	周成, 孙恺庭, 李江, 等.基于数字孪生的车间三维可视化监控系统[J/OL]. [2020-11-04]. 计算机集成制造系统.http://kns.cnki.net/kcms/detail/11.5946.TP.20200817.0917.008.html.
[13]	樊启祥, 林鹏, 魏鹏程, 等.智能建造闭环控制理论[J/OL]. [2020-11-04].清华大学学报(自然科学版). https://doi.org/10.16511/j.cnki.qhdxxb.2020.26.023.
[14]	江丰光, 熊博龙, 张超.我国人工智能如何实现战略突破:基于中美4份人工智能发展报告的比较与解读[J]. 现代远程教育研究, 2020, 32(1):3-11.
[15]	闫纪红, 李柏林.智能制造研究热点及趋势分析[J]. 科学通报, 2020, 65(8):684-694.
[16]	三局工程管理学部办公室.中国工程院重点咨询项目《中国建造2035战略研究》会暨中国工程院院士重庆行系列活动在渝举行[EB/OL].[2020-04-07 ]. http://www.cae.cn/cae/html/main/col110/2019G05/07/20190507142610206746869_1.html.
[17]	刘占省, 王竞超, 韩泽斌, 等.车辐式索桁架长度误差敏感性试验及可靠性评估[J]. 天津大学学报(自然科学与工程技术版), 2019, 52(增刊2):23-30.
[18]	郭彦林, 张旭乔.温度作用和索长误差对采用定长索设计的张拉结构影响研究[J]. 土木工程学报, 2017, 50(6):11-22 , 61.
[19]	周浩, 杜咏, 李国强, 等.预应力钢绞线温度膨胀及高温蠕变性能试验研究[J]. 工程力学, 2018, 35(6):123-131.
[20]	陈志华, 王霄翔, 刘红波, 等.张弦结构体系全寿命预应力损失模型分析[J]. 工业建筑, 2015, 45(8):25-29 , 138.
[21]	聂珲, 陈海峰.基于NB-IoT环境监测的多传感器数据融合技术[J]. 传感技术学报, 2020, 33(1):144-152.
[22]	周一一, 舒展, 周昌风, 等.基于智能建造的负泊松比耗能钢板的形式设计及优化[J]. 工业建筑, 2020, 50(2):137-142 , 157.
[23]	LIU Z S, SHI G L, ZHANG A S, et al. Intelligent Tensioning Method for Prestressed Cables Based on Digital Twins and Artificial Intelligence[J]. Sensors, 2020, 20(24).DOI: 10.3390/s20247006.
[24]	严仁章, 万里源, 周建庭, 等.索拱桁架-单层网壳复合空间结构的结构设计与稳定性分析[J]. 工业建筑, 2020, 50(4):103-110.
[25]	刘占省, 张安山, 王文思, 等.数字孪生驱动的冬奥场馆消防安全动态疏散方法[J]. 同济大学学报(自然科学版), 2020, 48(7):962-971.
[26]	熊超华, 骆汉宾.施工现场作业环境监测数据融合预警方法研究[J]. 施工技术, 2018, 47(23):125-129.
[27]	LI Y, JIA H L, QI J T, et al. An Acquisition Method of Agricultural Equipment Roll Angle Based on Multi-Source Information Fusion[J]. Sensors, 2020, 20(7).DOI: 10.3390/s20072082.