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Derivation of a new parametric impulse response matrix utilized for nodal wind load identification by response measurement

机译:通过响应测量推导用于节点风载荷识别的新参数脉冲响应矩阵

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摘要

This paper provides new formulations to derive the impulse response matrix, which is then used in the problem of load identification with application to wind induced vibration. The applied loads are inversely identified based on the measured structural responses by solving the associated discrete ill-posed problem. To this end — based on an existing parametric structural model — the impulse response functions of acceleration, velocity and displacement have been computed. Time discretization of convolution integral has been implemented according to an existing and a newly proposed procedure, which differ in the numerical integration methods. The former was evaluated based on a constant rectangular approximation of the sampled data and impulse response function in a number of steps corresponding to the sampling rate, while the latter interpolates the sampled data in an arbitrary number of sub-steps and then integrates over the sub-steps and steps. The identification procedure was implemented for a simulation example as well as an experimental laboratory case. The ill-conditioning of the impulse response matrix made it necessary to use Tikhonov regularization to recover the applied force from noise polluted measured response. The optimal regularization parameter has been obtained by L-curve and GCV method. The results of simulation represent good agreement between identified and measured force. In the experiments the identification results based on the measured displacement as well as acceleration are provided. Further it is shown that the accuracy of experimentally identified load depends on the sensitivity of measurement instruments over the different frequency ranges.
机译:本文提供了新的公式来导出脉冲响应矩阵,然后将其用于载荷识别问题并应用于风振。通过解决相关的离散不适定问题,可以基于测得的结构响应来反向识别施加的载荷。为此,基于现有的参数结构模型,已计算出加速度,速度和位移的脉冲响应函数。卷积积分的时间离散化已经根据现有和新提出的程序来实现,它们在数值积分方法上有所不同。前者是根据采样数据和脉冲响应函数的恒定矩形近似值按照对应于采样率的多个步长进行评估的,而后者则以任意数量的子步长对采样数据进行插值,然后在子步长上积分-步骤和步骤。识别程序适用于仿真示例和实验实验室案例。脉冲响应矩阵的不适使必须使用Tikhonov正则化来从噪声污染的测量响应中恢复作用力。通过L曲线和GCV方法获得了最佳的正则化参数。仿真结果表明,确定的力和测量的力之间具有良好的一致性。在实验中,提供了基于测得的位移和加速度的识别结果。进一步表明,实验确定的负载的精度取决于不同频率范围内测量仪器的灵敏度。

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