A Numerical and Experimental Investigation of the Most Fundamental Time-Domain Input-Output System Identification Methods for the Normal Modal Analysis of Flexible Structures.

IF 3.5 3区 综合性期刊 Q2 CHEMISTRY, ANALYTICAL Sensors Pub Date : 2025-02-19 DOI:10.3390/s25041259
Şefika İpek Lök, Carmine Maria Pappalardo, Rosario La Regina, Domenico Guida
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Abstract

This paper deals with developing a comparative study of the principal time-domain system identification methods suitable for performing an experimental modal analysis of structural systems. To this end, this work focuses first on analyzing and reviewing the mathematical background concerning the analytical methods and the computational algorithms of interest for this study. The methods considered in the paper are referred to as the AutoRegressive eXogenous (ARX) method, the State-Space ESTimation (SSEST) method, the Numerical Algorithm for Subspace State-Space System Identification (N4SID), the Eigensystem Realization Algorithm (ERA) combined with the Observer/Kalman Filter Identification (OKID) method, and the Transfer Function ESTimation (TFEST) method. Starting from the identified models estimated through the methodologies reported in the paper, a set of second-order configuration-space dynamical models of the structural system of interest can also be determined by employing an estimation method for the Mass, Stiffness, and Damping (MSD) matrices. Furthermore, in practical applications, the correct estimation of the damping matrix is severely hampered by noise that corrupts the input and output measurements. To address this problem, in this paper, the identification of the damping matrix is improved by employing the Proportional Damping Coefficient (PDC) identification method, which is based on the use of the identified set of natural frequencies and damping ratios found for the case study analyzed in the paper. This work also revisits the critical aspects and pitfalls related to using the Model Order Reduction (MOR) approach combined with the Balanced Truncation Method (BTM) to reduce the dimensions of the identified state-space models. Finally, this work analyzes the performance of all the fundamental system identification methods mentioned before when applied to the experimental modal analysis of flexible structures. This is achieved by carrying out an experimental campaign based on the use of a vibrating test rig, which serves as a demonstrative example of a typical structural system. The complete set of experimental results found in this investigation is reported in the appendix of the paper.

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用于柔性结构法向模态分析的最基本时域输入输出系统识别方法的数值和实验研究》(A Numerical and Experimental Investigation of the Most Fundamental Time-Domain Input-Output System Identification Methods for the Normal Modal Analysis of Flexible Structures)。
本文对适用于结构系统试验模态分析的主要时域系统辨识方法进行了比较研究。为此,本工作首先着重分析和回顾本研究的分析方法和计算算法的数学背景。本文考虑的方法包括自回归外生(ARX)方法、状态空间估计(SSEST)方法、子空间状态空间系统识别数值算法(N4SID)、结合观测器/卡尔曼滤波识别(OKID)方法的特征系统实现算法(ERA)和传递函数估计(TFEST)方法。从通过本文报告的方法估计的识别模型开始,也可以通过采用质量,刚度和阻尼(MSD)矩阵的估计方法确定一组感兴趣的结构系统的二阶构型空间动力学模型。此外,在实际应用中,干扰输入和输出测量的噪声严重妨碍了对阻尼矩阵的正确估计。为了解决这一问题,本文采用比例阻尼系数(PDC)识别方法改进了阻尼矩阵的识别,该方法基于为本文分析的案例研究找到的识别集的固有频率和阻尼比。这项工作还回顾了与使用模型降阶(MOR)方法结合平衡截断方法(BTM)来降低已识别状态空间模型的维度相关的关键方面和陷阱。最后,本文分析了上述所有基本系统识别方法在柔性结构模态试验分析中的性能。这是通过基于使用振动试验台的实验活动来实现的,该试验台作为典型结构系统的示范示例。在本文的附录中报告了本次调查中发现的全套实验结果。
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来源期刊
Sensors
Sensors 工程技术-电化学
CiteScore
7.30
自引率
12.80%
发文量
8430
审稿时长
1.7 months
期刊介绍: Sensors (ISSN 1424-8220) provides an advanced forum for the science and technology of sensors and biosensors. It publishes reviews (including comprehensive reviews on the complete sensors products), regular research papers and short notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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