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1D system identification of buildings during earthquakes by seismic interferometry with waveform inversion of impulse responses-method and application to Millikan library

机译:地震响应法与脉冲响应法波形反演的地震一维建筑物识别方法及其在密立根图书馆的应用

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Two new algorithms have been introduced as a further development of a robust interferometric method for structural health monitoring (SHM) of buildings during earthquakes using data from seismic sensors. The SHM method is intended to be used in an automatic seismic alert system, to issue a warning of significant damage during or immediately after the earthquake, and facilitate decision making on evacuation, to avoid loss of life and injury from possible collapse of the weekend structure during aftershock shaking. The method identifies a wave velocity profile of the building by fitting an equivalent layered shear beam model in impulse response functions (virtual source at roof) of the recorded earthquake response. The structural health is monitored by detecting changes in the identified velocities in moving time windows, the initial window being used as reference. Because the fit involves essentially matching phase difference between motion at different floors, the identified velocity profile is not affected by rigid body rocking, and soil-structure interaction in general, as demonstrated in this paper. Consequently, detected changes in wave velocity during an earthquake are not affected by changes in the soil-foundation system, which is a major advantage over SHM by detecting changes in the observed modal frequencies. Further, the method is robust when applied to real buildings and large amplitude earthquake response, as demonstrated in previous work. The new fitting algorithms introduced are the nonlinear least squares (LSQ) fit and the time shift matching (TSM) algorithms. The former involves waveform inversion of the impulse responses, and the latter - iterative matching of the pulse time shifts, both markedly reducing the identification error as compared to the previously used direct ray algorithm, especially for more detailed models, i.e., with fewer floors per layer. Results are presented of identification of the NS, EW and torsional responses of the densely instrumented Millikan Library (9-story reinforced concrete building in Pasadena, California) during a small earthquake.
机译:引入了两种新算法,作为一种稳健的干涉测量方法的进一步发展,该方法用于使用地震传感器的数据在地震过程中对建筑物进行结构健康监测(SHM)。 SHM方法旨在用于自动地震警报系统中,以在地震发生期间或地震发生后立即发出重大损坏的警告,并便于疏散决策,避免周末结构可能倒塌而造成人员伤亡在余震中。该方法通过在记录的地震响应的脉冲响应函数(屋顶的虚拟源)中拟合等效层状剪切梁模型来识别建筑物的波速分布。通过在移动的时间窗口(初始窗口用作参考)中检测到的速度变化来监视结构的健康状况。因为拟合涉及在不同楼层之间的运动之间基本匹配的相位差,所以本文确定的速度分布不受刚体摇摆和土壤-结构相互作用的影响。因此,地震过程中检测到的波速变化不受土壤-基础系统变化的影响,这是通过检测观测到的模态频率变化而超过SHM的主要优势。此外,该方法在应用于实际建筑物和大振幅地震响应时具有鲁棒性,如先前的工作所示。引入的新拟合算法是非线性最小二乘(LSQ)拟合和时移匹配(TSM)算法。前者涉及脉冲响应的波形求逆,而后者涉及脉冲时间偏移的迭代匹配,与以前使用的直接射线算法相比,两者都显着减少了识别误差,尤其是对于更详细的模型,即每层地板更少层。给出了在小地震期间密实仪器密立根图书馆(加利福尼亚州帕萨迪纳的9层钢筋混凝土建筑)的NS,EW和扭转响应的识别结果。

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