PARAMETRIC TIME-DOMAIN METHODS FOR THE IDENTIFICATION OF VIBRATING STRUCTURES—A CRITICAL COMPARISON AND ASSESSMENT
PARAMETRIC TIME-DOMAIN METHODS FOR THE IDENTIFICATION OF VIBRATING STRUCTURES—A CRITICAL COMPARISON AND ASSESSMENT
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DOI：
10.1006/mssp.2001.1424
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发表时间：
2001-11
影响因子：
8.4
通讯作者：
K. Petsounis;S. Fassois
中科院分区：
文献类型：
--
作者：
K. Petsounis;S. Fassois
本文对四种随机方法(PEM，2SLS，LMS，IV)和三种确定性方法(LS，Prony，ERA)从随机激励和噪声污染的响应信号中识别振动结构的参数时域进行了关键的比较。文中对这些方法进行了简要的总结，重点介绍了这些方法的原理和实现方法，而本文的研究是基于一个六自由度结构模型，该模型具有两个紧密间隔的振型、两个弱振型和较大范围的振型阻尼。在两种不同的(宽带/窄带)噪声环境下进行了蒙特卡罗实验，并与非参数频域识别进行了比较。随机方法--最著名的是PEM、LMS和IV--以增加复杂性为代价，被证明在不可忽略的噪声情况下具有潜在优势，而确定性方法--最明显的是Prony和ERA--在可以忽略的噪声情况下可能就足够了。此外：(A)模型阶次估计被证明不是直截了当的，需要大量的超定(特别是最小二乘法)。(B)弱的近距离模很难识别，而确定性方法和2SLS完全忽略了它。(C)高度衰减的模式也存在一些困难(主要是对LS而言)。(D)出现错误模式，主要表现为LS(宽带噪声)和ERA(窄带噪声)。(E)固有频率的估计精度一般较高，阻尼比的估计精度较低，残差(振型)的估计精度更低。此外，对于紧密间隔的模式，精度略低，对于两个高度衰减的模式，精度显著降低。(F)PEM、LMS和IV实现了较低的偏置误差和良好的总体精度，其次是2SLS、Prony、ERA，最后是LS。(G)不稳定模主要表现在IV和ERA上。(H)所有方法似乎都对选定的模型顺序和设计参数敏感，用户的专业知识是必要的。
Abstract A critical comparison of four stochastic (PEM, 2SLS, LMS, IV) and three deterministic (LS, Prony, ERA) methods for the parametric time-domain identification of vibrating structures from random excitation and noise-corrupted response signals is presented. Concise summaries of the methods, highlighting their principles and realisations, are provided, while the study is based upon a six-degree-of-freedom structural model characterised by two closely spaced modes, two weak modes and a wide range of modal damping. Monte-Carlo experiments under two different (wideband/narrowband) noise environments are performed, along with comparisons with non-parametric frequency domain identification. The stochastic methods—most notably PEM, LMS and IV—are, at the price of increased complexity, shown to lead to potential advantages in non-negligible noise cases, while deterministic methods—most notably Prony and ERA—may suffice under negligible noise. In addition: (a) Model order estimation is shown not to be straightforward, and significant overdetermination is required (especially by the LS). (b) A weak closely spaced mode is hard to identify, while being completely missed by the deterministic methods and the 2SLS. (c) A highly damped mode presents some difficulty as well (mainly for the LS). (d) False modes are exhibited, primarily by the LS (wideband noise) and the ERA (narrowband noise). (e) The achievable estimation accuracy is generally high for the natural frequencies, lower for the damping ratios, and even more so for the residues (mode shapes). Furthermore, accuracy is somewhat lower for the closely spaced modes and significantly lower for the two highly damped modes. (f) PEM, LMS and IV achieve lower bias errors and good overall accuracy, followed by the 2SLS, Prony, ERA and, finally, LS. (g) Unstable modes are mainly exhibited by the IV and ERA. (h) All methods appear sensitive to the selected model order and design parameters, and user expertise is necessary.