基于随机子空间的递推在线模态识别算法

张家滨;陈国平

振动与冲击 ›› 2009, Vol. 28 ›› Issue (8) : 42-45.

PDF(1644 KB)
PDF(1644 KB)
振动与冲击 ›› 2009, Vol. 28 ›› Issue (8) : 42-45.
论文

基于随机子空间的递推在线模态识别算法

  • 张家滨1,陈国平1
作者信息 +

STOCHASTIC SUBSPACE-BASED ON-LINE RECURSIVE MODAL IDENTIFICATION METHOD

  • ZHANG JIABIN1, CHEN GUOPING1
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文章历史 +

摘要

摘要:基于随机子空间算法,根据矩阵空间的性质,利用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,实现了单独利用响应数据,在线识别模态参数的方法。最后通过仿真算例,利用算法跟踪不断改变的模态空间和时变模态参数,验证方法的有效性及稳定性。

Abstract

Abstract: Based on the stochastic subspace method, using the property of matrix space, the projection from future data row space to past data row space is modified to an update mode for subspace tracking though QR decomposition. The left singular vector of the projection has been tracked by subspace tracking algorithm. Then the modal parameter is obtained by least square method. online modal parameter identification is Realized by output-data only. At last though an experiment, the efficiency and stability of the method has been proved by tracking the changing of the modal space and the modal parameter.

关键词

随机子空间 / WINC(weighted information criterion) / 子空间跟踪 / 模态识别 / 环境激励 / 非稳态

Key words

stochastic subspace / WINC(weighted information criterion) / subspace tracking / modal analysis

引用本文

导出引用
张家滨;陈国平. 基于随机子空间的递推在线模态识别算法 [J]. 振动与冲击, 2009, 28(8): 42-45
ZHANG JIABIN;CHEN GUOPING. STOCHASTIC SUBSPACE-BASED ON-LINE RECURSIVE MODAL IDENTIFICATION METHOD[J]. Journal of Vibration and Shock, 2009, 28(8): 42-45

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