快速特征系统实现算法用于环境激励下的结构模态参数识别

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摘要对特征系统实现算法（ERA）进行了改进，采用对构建的新对称矩阵进行特征值分解来替代Hankel矩阵的奇异值分解，提出了计算速度更快、数据储存更少的快速特征系统实现算法（FERA）。首先利用已知的4层框架进行数值模拟，对其施加缩尺的El Centro地震作为未知激励，采用FERA和ERA算法对仿真所得的位移、速度和加速度分别进行模态参数识别，与理论值进行对比结果显示：FERA算法适用于任何动力响应对结构进行模态参数识别，并且其运算速度可较ERA算法有较大提高。此外，FERA算法还被运用到了一座运营中的人行桥环境激励试验中，结果表明该算法同样适用于实际结构的模态参数识别。

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	蒲黔辉
	洪彧1
	王高新2
	李晓斌1

关键词 ：快速特征系统实现, 环境激励, 动力响应, 模态参数识别

Abstract：The proposed fast eigensystem realization algorithm (FERA) is an improvement of the ERA, which can improve the calculation efficiency and cut down the data storage. To avoid the singular value decomposition of Hankel matrix, the eigenvalue decomposition of a newly built symmetric matrix was adopted in the method. Asimulated fourstory frame structure was utilized for validating the accuracy and efficiency of the FERA method. The scaled El Centro earthquake was applied to the structure as an unknown excitation. Both FERA and ERA methods were used for extracting the modal parameters from the simulated displacements, velocities and accelerations, respectively. After comparing the modal analysis results with the analytical values, the conclusions show that the FERA can accurately identify modal parameters from any type of dynamic responses, and the computational speed can increase rapidly. In addition, the FERA was used for extracting modal parameters of an inservice pedestrian bridge through ambient test, and the results show that the proposed method can also work for the actual structure.

Key words： FERA ambient excitation dynamic response;modal parameter identification

收稿日期: 2017-01-18 出版日期: 2018-03-15

引用本文:

蒲黔辉,洪彧1，王高新2，李晓斌1. 快速特征系统实现算法用于环境激励下的结构模态参数识别[J]. 振动与冲击, 2018, 37(6): 55-60.
PU Qianhui1，HONG Yu1，WANG Gaoxin2，LI Xiaobin1. Fast eigensystem realization algorithm based structural modal parameters identification for ambient tests. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(6): 55-60.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2018/V37/I6/55

[1] James III G H, Carne T G, Lauffer J P. The natural excitation technique (NExT) for modal parameter extraction from operating wind turbines[R]. No. SAND-92-1666, Sandia National Labs., Albuquerque, NM (United States), 1993.
[2] James G H, Carne T G, Lauffer J P, et al. Modal testing using natural excitation[C]//Proceedings of the international modal analysis conference. SEM society for experimental mechanics Inc., 1992. 1208-1208.
[3] Ibrahim S R, Mikulcik E C. A method for the direct identification of vibration parameters from the free response[J]. The shock and vibration bulletin, 1977, 47(4):183-198.
[4] 杨佑发，李帅，李海龙. 环境激励下结构模态参数识别的改进ITD法[J]. 振动与冲击, 2014(1):194-199.
Yang You-fa, Li shuai, Li hai-long. Improved ITD method for structural modal parameter identification under ambient excitation [J]. Journal of vibration and shock,2014(1):194-199.
[5] Juang J N, Pappa R S. An eigensystem realization algorithm for modal parameter identification and model reduction [J]. Journal of guidance, control, and dynamics, 1985, 8(5): 620-627.
[6] Juang J N, Pappa R S. Effects of noise on modalparameters identified by the eigensystem realizationalgorithm [J]. Journal of Guidance Control andDynamics, 1986, 9(3): 294-303.
[7]祁泉泉，辛克贵，崔定宇.扩展特征系统实现算法在结构模态参数识别中的应用[J]. 工程力学,2011,28(3): 29-34.
Qi Quan-quan, Xin Ke-gui, Cui Ding-yu. The application of the extended eigensystem realization algorithm for structural modal parameter identification [J]. Engineering Mechanics, 2011, 28(3): 29-34.
[8] 崔定宇，辛克贵，祁泉泉.扩展特征系统实现算法的模态参数识别特性研究 [J]. 工程力学, 2013, 30(8): 49-53.
Cui Ding-yu,Xin Ke-gui,Qi Quan-quan. Modal parameter identification research for the extended eigensystem realization algorithm [J]. Engineering Mechanics, 2013, 30(8): 49-53.
[9]辛峻峰, 张永波, 盛进路. 一种改进的特征系统实现算法及其在海洋平台上的应用[J]. 振动与冲击, 2015(24):197-201.
Xin Jun-feng, Zhang Yong-bo, Sheng Jin-lu. Improved eigen system realization algorithm and its application in the analysis of ocean platform [J]. Journal of vibration and shock, 2015(24):197-201.
[10] 包兴先，李昌良，刘志慧. 基于低秩Hankel矩阵逼近的模态参数识别方法 [J]. 振动与冲击,2014, 33(20): 57-62.
Bao Xing-xian, Li Chang-liang, & Liu Zhi-hui. Modal parameters identification based on low rank approximation of a Hankel matrix [J]. Journal of vibration and shock, 2014, 33(20): 57-62.
[11] Reynders E. System identification methods for (operational) modal analysis: review and comparison[J]. Archives of Computational Methods in Engineering, 2012, 19(1): 51-124.
[12]刘宇飞, 辛克贵, 樊健生,崔定宇. 环境激励下结构模态参数识别方法综述[J]. 工程力学, 2014, 31(4):46-53.
Liu Yu-fei , Xin Ke-gui, Fan Jian-sheng, Cui Ding-yu. A review of structure modal identification methodsthrough ambient excitation [J]. Engineering mechanics, 2014, 31(4):46-53.
[13] Caicedo J M. Practical guidelines for the natural excitation technique (NExT) and the eigensystem realization algorithm (ERA) for modal identification using ambient vibration[J]. Experimental Techniques, 2011, 35(4): 52-58.
[14] Hong Y, Liu X, Dong X, et al. Experimental model updating using frequency response functions[C]//Lynch J P. Proceedings of SPIE: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems. Las Vegas: 2016. 980325.
[15] Allemang, R J, Brown, D L. A correlation coefficient for modal vector analysis[C]// Proceedings of the 1st international modal analysis conference. Orlando: 1982. 110-116.
[16] Zhu D, Guo J, Wang Y, et al. Field validation of flexure-based mobile sensing nodes on a space frame bridge[C]// Proceedings of the 8th International Workshop on Structural Health Monitoring.Stanford: 2011.13-15.
[17]Zhu D, Cho C, Wang Y. Finite element model updating of a space frame bridge with mobile sensing data[C]// Proceedings of SPIE, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems. San Diego: 2012. 8345:834513.