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Tracking modal parameters from building seismic response data using recursive subspace identification algorithm

机译：使用递归子空间识别算法从建筑物地震响应数据中跟踪模态参数

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摘要

Tracking modal parameters and estimating the current structural state of a building from seismic response measurements, particularly during strong earthquake excitations, can provide useful information for building safety assessment and the adaptive control of a structure. Therefore, online or recursive identification techniques need to be developed and implemented for building seismic response monitoring. This paper develops and examines different methods to track modal parameters from building seismic response data. The methods include recursive data-driven subspace identification (RSI-DATA) using Givens rotation algorithm, and RSI-DATA using Bona fide algorithm. The question on how well the results of RSI-DATA reflect the real condition is investigated and verified with a bilinear SDOF simulation study. Time-varying modal parameters of a four-story reinforced concrete school building are identified based on a series of earthquake excitations, including several seismic events, large and small. Discussions on the different methods' ability to track the time-varying modal parameters are presented. The variation of the identified building modal frequencies and damping ratios from a series of event-by-event seismic responses, particularly before and after retrofitting of the building is also discussed. Copyright (C) 2017 John Wiley & Sons, Ltd.
机译：跟踪模态参数并从地震响应测量值估计建筑物的当前结构状态，尤其是在强烈地震激发期间，可以为建筑物安全评估和结构的自适应控制提供有用的信息。因此，需要开发和实施在线或递归识别技术以用于建筑物地震响应监测。本文开发并研究了从建筑物地震响应数据中跟踪模态参数的不同方法。这些方法包括使用Givens旋转算法的递归数据驱动子空间识别（RSI-DATA）和使用Bona fide算法的RSI-DATA。 RSI-DATA的结果如何反映真实条件的问题已通过双线性SDOF模拟研究进行了调查和验证。基于一系列地震激励（包括多个大小事件），确定了四层钢筋混凝土教学楼的时变模态参数。讨论了不同方法跟踪时变模态参数的能力。还讨论了一系列事件之间的地震响应，尤其是在建筑物翻新前后，所识别的建筑物模态频率和阻尼比的变化。版权所有（C）2017 John Wiley＆Sons，Ltd.

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