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作 者:罗尧治[1] 赵靖宇 LUO Yaozhi;ZHAO Jingyu(Space Structure Research Center,Zhejiang University,Hangzhou 310058,China)
机构地区:[1]浙江大学空间结构研究中心,浙江杭州310058
出 处:《建筑结构学报》2022年第10期16-28,共13页Journal of Building Structures
基 金:浙江省重点研发计划(2021C03154);国家重点研发计划(2017YFC0806100,2021YFF0501001)。
摘 要:空间结构是大跨度、大空间和大面积建筑结构的主要形式,在国家基础设施与城市建设领域有广泛应用,其结构安全性至关重要。空间结构健康监测通过传感技术准确获取结构响应,实时反映结构的性能状态,为空间结构施工、运营与管理决策提供科学的依据与指导。经过多年的研究和工程实践,已经发展了适合大型空间结构的物联网无线传感监测技术,建立了多维数据分析理论,并在国家体育场、国家速滑馆、北京大兴国际机场航站楼等重大工程中实现规模化应用,取得了阶段性研究进展。通过对空间结构健康监测的研究及应用现状进行系统总结,疏理空间结构健康监测的特点,围绕荷载与响应多维传感及大面域传输网络综述了其传感监测技术的研究现状,归纳了结构荷载分析、响应分析以及结构状态评估的监测数据分析理论。同时,基于融合大数据、云计算以及人工智能展望其未来研究方向,旨在进一步推动空间结构健康监测的创新与发展。Space structures are the main form of long-span, large-space, and large-area building structures, which are widely used in national infrastructure and urban construction, and their structural safety is of paramount importance. Space structure health monitoring(SSHM) accurately obtains structural responses through sensing technology, reflects the performance state of the structure in real-time, and provides a scientific basis and guidance for the construction, operation, and management decision of space structures. After years of research and engineering practice, wireless-sensor technology based on the internet of things has been developed, which is suitable for large-span space structures. Multi-dimensional data analysis theory has been proposed, and the large-scale applications have been implemented in major projects such as the National Stadium, the National Speed Skating Oval, and the Beijing Daxing International Airport Terminal Building, the research progress has been achieved. By systematically summarizing the current research and applications of SSHM, the characteristics of SSHM are clarified, and the current research situation of the sensing technology is reviewed around the multi-dimensional sensing of load and response, as well as the large-area transmission networks. The monitoring data analysis theories are summarized, including structural load analysis, response analysis, and structural condition assessment. Meanwhile, future research directions are foreseen based on the integration of big data, cloud computing, and artificial intelligence, aiming to further promote the innovation and development of SSHM.
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