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作 者:刘占省[1] 史国梁 王竞超 LIU Zhansheng;SHI Guoliang;WANG Jingchao(College of Architecture,Civil and Transportation Engineering,Beijing University of Technology,Beijing 100124,China)
出 处:《工业建筑》2021年第5期1-9,123,共10页Industrial Construction
基 金:国家重点研发计划科技冬奥专项(2018YFF0300300)。
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。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.
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