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为了研究非平稳环境激励下只根据响应信号识别系统的模态参数的问题,首先将自然激励技术(natural excitation technique,NExT)法的应用范围从理想白噪声扩展到了MA(q)模型。假设非平稳激励由(d-1)阶多项式趋势项与MA(q)模型之和构成,将其d阶差分后变成MA(q+d)阶模型;导出了基于激励和响应差分数据的运动方程,建立了非平稳环境激励下模态参数识别NExT法。用该方法对龙潭河大桥进行模态参数识别。识别的结果与有限元计算值一致,并且在非平稳环境激励下,该方法能够比标准NExT方法获得更好的模态参数识别结果。
In order to study the modal parameters of system recognition based on response signals under non-stationary environment excitation, the application of natural excitation technique (NExT) is extended from ideal white noise to MA (q) model. Assuming that the non-stationary stimulus consists of the sum of the (d-1) -th order polynomial trend and the MA (q) model, the d-order difference is transformed into the MA (q + d) order model. Based on the stimulus and response difference data The equations of motion are established, and the NExT method for modal parameter identification under non-stationary environment excitation is established. This method is used to identify the modal parameters of Longtan River Bridge. The recognition result is consistent with the finite element calculation, and under non-stationary environmental excitation, the method can obtain better modal parameter identification results than the standard NExT method.