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基于R-TPBSS的结构模态参数识别方法
引用本文:杨彦龙,程伟.基于R-TPBSS的结构模态参数识别方法[J].振动与冲击,2012,31(10):9-12,28.
作者姓名:杨彦龙  程伟
作者单位:北京航空航天大学 航空科学与工程学院,北京 100191
摘    要:提出了一种基于R-TPBSS算法的结构模态参数识别方法。该方法通过对响应信号进行稳健性白化处理,提高了算法的抗噪性。该方法将模态坐标和模态振型分别视为独立源信号和混合矩阵,以模态坐标的时间预测性大于响应信号的时间预测性为前提构造目标函数,通过优化目标函数,直接从结构自由响应中分离出各个模态,配合单点模态参数识别方法,提取出结构的模态参数。仿真结果表明,此方法具有很高的识别精度,对噪声很好的鲁棒性,密集模态下,同样能够准确的识别出结构的模态参数。

关 键 词:稳健TPBSS算法    模态参数识别    盲源分离    鲁棒性    密集模态  
收稿时间:2011-4-7
修稿时间:2011-6-8

Modal parameter identification based on robust blind source separation using temporal predictability
YANG Yan-long,CHENG Wei.Modal parameter identification based on robust blind source separation using temporal predictability[J].Journal of Vibration and Shock,2012,31(10):9-12,28.
Authors:YANG Yan-long  CHENG Wei
Affiliation:(School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China)
Abstract:A method of robust blind source separation using temporal predictability(R-TPBSS) was taken in use for modal parameter identification.In order to improve noise immunity of the algorithm,a robust whitening process was performed to reduce the noise in the measured vibration signals.In the method,the(inverse) modal shapes and the modal responses were regarded as a mixed matrix and source signals respectively.The objective function was constructed under the assumption that the temporal predictability of any physical response is less than(or equal to) that of any of its modal responses.Then,all the modal shapes were recovered directly from free responses by optimizing the objective function.Finally,frequencies and damping ratios were obtained from the modal responses by use of simple single degree of freedom methods.Numerical evaluations demonstrate that the mode shapes can be extracted exactly even in the case of low signal to noise rate(SNR) or closely spaced modes.
Keywords:robust TPBSS  modal parameter identification  blind source separation  robustness  closely spaced modes
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