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On-line environmental noise driven 3-DOF per story parametric identification of a building

机译:在线环境噪声驱动的建筑物每层3 DOF参数识别

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Feasibility of recovering the parameters of a shear building model with three degrees of freedom per story using a least squares with forgetting factor algorithm is analyzed. Two orthogonal horizontal seismic signals, known as environmental noise, are used as excitation for the algorithm. Environmental noise are small magnitude signals induced by several causes: sensor noise, wind effects, machinery operation, vehicular traffic and others phenomena. These signals, in contrast with seismic excitation, do not produce structural damage and are easy to obtain by installing accelerometers on the building. The aim of this work is to show that these signals still contain relevant information related with building dynamic's response, and that with proper use of identification algorithms, precise information about the building model parameters can be obtained for use in the design of vibration control algorithms. As the identification with small magnitude signals can be executed on line before a large earthquake occurs, calculation of proper control signals would not have to wait for the results of an identification excited by a strong seismic signal, saving critical time and helping to avoid structure damage.
机译:分析了使用带有遗忘因子算法的最小二乘恢复每个楼层三个自由度的剪切建筑模型的参数的可行性。该算法使用两个正交的水平地震信号(称为环境噪声)作为激励。环境噪声是由多种原因引起的小信号:传感器噪声,风影响,机械操作,车辆通行和其他现象。与地震激励相反,这些信号不会产生结构破坏,并且很容易通过在建筑物上安装加速度计来获得。这项工作的目的是表明这些信号仍然包含与建筑物动力响应相关的相关信息,并且通过正确使用识别算法,可以获得有关建筑物模型参数的精确信息,以用于振动控制算法的设计。由于小震级信号的识别可以在大地震发生之前在线进行,因此适当的控制信号的计算将不必等待强震信号激发的识别结果,从而节省了关键时间并有助于避免结构损坏。

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