Long-Term Seismic Monitoring of a Passively-Controlled Steel Building on Performance Assessment under Strong Earthquake

IF 5.4 2区 工程技术
Yunjia Tong, Songtao Xue, Liyu Xie, Hesheng Tang
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引用次数: 0

Abstract

Analysis of recorded seismic response of an eight-story passively-controlled steel building located in Sendai is reported in this paper. Vibration monitoring system has been instrumented to test the effectiveness of dampers and actual performance of passively-controlled structures under earthquake since it was constructed in 2003. A data-driven stochastic subspace identification methodology with an alternative strategy to remove spurious modes is developed and implemented to the recorded actual earthquake response to extract dynamic properties of the passively-controlled eight-story steel building from the recorded floor acceleration data. Thus, the inherent damping characteristic of the building is identified under various earthquakes. Moreover, the variation of the estimated natural frequencies, mode shapes, and damping ratios for all the earthquake recordings are illustrated. To further investigate serviceability of the passively-controlled steel building during an earthquake, probabilistic model updating is developed to estimate the model parameters and infer the response of the structure based on the identified modes. Besides, seismic performance assessment of the passively-controlled steel building from the estimated dynamic characteristics and model parameters during service period is also discussed.
某被动控制钢结构建筑在强震作用下的长期地震监测及性能评估
本文报道了仙台一座八层被动控制钢结构建筑的地震响应记录分析。自2003年建成以来,对被动控制结构进行了振动监测,以测试阻尼器的有效性和地震作用下的实际性能。提出了一种数据驱动的随机子空间识别方法,并将其应用于实际地震响应记录中,从记录的楼层加速度数据中提取被动控制的八层钢结构建筑的动力特性。因此,确定了建筑物在各种地震下的固有阻尼特性。此外,还说明了所有地震记录的估计固有频率、模态振型和阻尼比的变化。为了进一步研究被动控制钢结构建筑在地震作用下的适用性,采用概率模型更新方法估计模型参数,并根据识别出的模态推断结构的响应。此外,从估计的动力特性和模型参数出发,讨论了被动控制钢结构建筑在服役期间的抗震性能评价。
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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring Engineering-Building and Construction
自引率
13.00%
发文量
0
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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