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利用响应数据识别模态参数的子空间在线递推算法 被引量:4

An online subspace recursive method for modal identification using output data
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摘要 基于随机子空间算法,利用矩阵空间的性质和QR分解将行空间到过去行空间的投影展开为一种用于跟踪的修改递推模式。通过子空间跟踪算法,不断跟踪计算投影的左奇异值向量,再利用最小二乘法求出系统的模态参数,最后用悬臂梁作为实验模型,通过不断改变系统激励的频带范围,验证方法的有效性及稳定性。结果表明,只要选取适当的衰减系数,该方法就可以既保证一定的识别精度,又具有良好的跟踪特性。 Based on the stochastic subspace method, the projection from row space of future data to that of data is modified to an update mode for subspace tracking. The left singular vector of the projection has been tracked by the projection approximation subspace tracking algorithm. Then the modal parameters are obtained by least square method. At last an experiment is made using a cantilever beam to prove the efficiency and stability of the method by changing the frequency band of the exciting signal. The results show that good precision and stability can be obtained at the same time by choosing the appropriate forgetting factor.
出处 《振动工程学报》 EI CSCD 北大核心 2009年第1期26-30,共5页 Journal of Vibration Engineering
关键词 随机子空间 PAST 子空间跟踪 模态识别 stochastic subspace PAST subspace tracking modal identification
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参考文献10

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