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基于NEXT/ERA时域联合算法的模态参数识别
引用本文:王红伟.基于NEXT/ERA时域联合算法的模态参数识别[J].上海师范大学学报(自然科学版),2015,44(2):146-153.
作者姓名:王红伟
作者单位:上海师范大学
基金项目:MTS土木结构试验系统在桥墩低周反复试验中的准确性和稳定性研究(SK201420)
摘    要:归纳总结了NEXT法和特征系统实现算法的基本思想,以及实施的基本步骤.在此基础上,基于matlab编制了模态识别程序.以东海大桥监测数据作为算例进行数值分析,成功识别了大桥的竖向振动动力学参数.识别结果可为桥梁动力特性计算,抗震分析,健康监测和损伤识别等提供基础数据.

关 键 词:模态参数    环境激励    结构模态
收稿时间:2014/2/21 0:00:00

Modal parameter identification based on NEXT/ERA time-domain joint algorithm
WANG Hongwei.Modal parameter identification based on NEXT/ERA time-domain joint algorithm[J].Journal of Shanghai Normal University(Natural Sciences),2015,44(2):146-153.
Authors:WANG Hongwei
Institution:Architecture Engineering College, Shanghai Normal University
Abstract:This paper summarizes the basic idea of NEXT algorithm and features of the system, and the basic steps of implementation.On this basis,a modal identification program is written using Matlab.The monitoring data of East China Sea bridge are selected as an example of numerical analysis.Dynamic parameters of vertical vibration of the bridge are successfully identified.The recognition results can be served for the dynamic characteristics of bridge seismic analysis, and to provide the basis data for health monitoring and damage identification.
Keywords:modal parameters  environmental incentive  structural modal
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