摘要
针对预应力钢结构力学参数实时变化导致安全性能分析与预测精度不足,无法实现结构的智能化安全控制,本文提出了数字孪生驱动的预应力钢结构安全智能控制方法.通过考虑结构安全状态的时空演化,形成基于数字孪生的安全智能控制框架,并将安全控制分为性能分析与预测两个方面.在控制框架的驱动下,研究了孪生模型的搭建机制并通过三维激光扫描技术和加权平均法修正模型提高保真性.基于三维激光扫描技术修正模型中关键节点坐标,有效降低了由施工误差导致的模型仿真误差.通过加权平均法综合考虑拉索的各个节点索力,修正模型中的构件尺寸,有效降低了因材料缺陷导致的模型仿真误差.依托孪生模型,精准获取表征结构安全的力学参数,为结构的安全分析与预测提供了数据支撑.融合D-S证据理论分析结构的安全状况,找到结构体系中最关键的受力构件及力学参数变化程度最高的节点.在结构安全性能预测过程中,建立数字孪生与随机森林的融合机理,分析各类因素对结构安全性能的影响程度并调整关键影响因素,预测结构的安全性能,最终形成结构安全控制机制.通过给出结构安全维护措施,有效地保证了结构的安全性.以轮辐式索桁架为研究对象,进行了方法的应用,验证了数字孪生在结构安全控制方面的有效性.
Real-time changes in the mechanical parameters of prestressed steel structures can limit the accuracy of the analysis and prediction of their performance,which in turn presents significant challenges to developing intelligent safety control systems for these structures.This study proposes a digital twin-based intelligent safety control system for prestressed steel structures.An intelligent safety control framework based on digital twins is established,considering the spatiotemporal evolution of structural safety.The safety control system is divided into two aspects:performance analysis and prediction.The construction of the twin model is analyzed,and the key node coordinates are corrected based on the control framework,three-dimensional laser scanning,and the weighted average method to reduce errors in the simulation.The weighted average method is used to comprehensively analyze the force on each node of the cable,and the component size in the correction model can effectively reduce the simulation errors caused by material defects.Accurate mechanical parameters of structural safety can be obtained using the twin model,providing data support for the analysis and prediction of structural safety.The D-S evidence theory is integrated to analyze the degree of safety of the structure as well as to determine the most critical force components and nodes with maximum change in their mechanical parameters.A method that combines digital twins and random forest techniques is established to analyze the influence of various factors on structural safety.The safety of the structure is predicted by adjusting the key influencing factors,and the structure safety control mechanism is finally formed.Based on this,the safety of the structure can be ensured by implementing structural safety maintenance measures.The effectiveness of digital twins in structural safety control was verified by applying it to the spoke-type cable truss.
作者
刘占省
史国梁
杜修力
孙哲
焦泽栋
Liu Zhansheng;Shi Guoliang;Du Xiuli;Sun Zhe;Jiao Zedong(Faculty of Architecture,Civil and Transportation Engineering,Beijing University of Technology,Beijing 100124,China;Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education,Beijing University of Technology,Beijing 100124,China)
出处
《天津大学学报(自然科学与工程技术版)》
EI
CAS
CSCD
北大核心
2023年第10期1043-1053,共11页
Journal of Tianjin University:Science and Technology
基金
国家自然科学基金资助项目(52178095)。
关键词
预应力钢结构
安全状态
数字孪生
机器学习
智能控制
prestressed steel structure
safe state
digital twins
machine learning
intelligent control