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本文针对结构模态参数辨识的噪声干扰问题,采用一种状态滤波方法削弱测量噪声的影响,避免了传统Kalman 滤波法中对系统模型的较高精度要求,并与特征系统实现算法(ERA)相结合,有效地克服了ERA 方法在信噪比较低的情况下对非零奇异值判断的困难,并更精确地识别出结构的模态参数。
Aiming at the problem of noise disturbance identified by structural modal parameters, a state filtering method is used to weaken the influence of measurement noise and avoids the high accuracy requirement of the traditional Kalman filter, which is compared with the ERA Combined with effectively overcome the ERA method to determine the non-zero singular value difficult in the case of low signal to noise ratio, and more accurately identify the structural modal parameters.