Smooth orthogonal decomposition-based vibration mode identification
Smooth orthogonal decomposition-based vibration mode identification
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DOI：
10.1016/j.jsv.2005.08.006
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发表时间：
2006-05-09
影响因子：
4.7
通讯作者：
Zhou, WL
中科院分区：
文献类型：
--
作者：
Chelidze, D;Zhou, WL
提出了一种新的多变量数据分析方法--平滑正交分解（SOD），用于提取多自由度分布参数振动系统的线性振型和固有频率。结果表明，对于多自由度系统的所有无阻尼自由振动，计算得到的光滑正交振型与实际振型直接对应，光滑正交值与相应的固有频率有关。同样的也被证明是真实的轻阻尼自由振动的集中和分布参数系统。与固有正交分解（POD）分析的固有局限性相反，POD分析需要系统的质量矩阵的知识来提取正常模式，并且不能唯一地识别具有相似的固有正交值的模态子空间，SOD克服了这两个缺陷。数值算例比较了POD和SOD在不同振动环境下的模态识别性能。(c)2005爱思唯尔有限公司保留所有权利。
A new multivariatc data analysis method called smooth orthogonal decomposition (SOD) is proposed to extract linear normal modes and natural frequencies of multi-degree-of-freedom and distributed-parameter vibration systems. It is demonstrated that for ail undamped free vibration of a multi-degree-of-freedoin system, the computed smooth orthogonal modes are in direct correspondence with the actual normal vibration modes and the smooth orthogonal values are related to the corresponding natural frequencies. The same is also shown to be true for lightly damped free vibrations of both lumped- and distributed-parameter systems. In contrast to the intrinsic limitations of the proper orthogonal decomposition (POD) analysis, which requires the knowledge of system's mass matrix to extract normal modes and cannot uniquely identify modal subspaces that have similar proper orthogonal values, the SOD is shown to overcome both of these deficiencies. Numerical examples are provided to compare the performances of the POD- and SOD-based modal identification in various types of vibration environment. (c) 2005 Elsevier Ltd. All rights reserved.