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超高耸钢结构的模态参数识别及模型修正

Modal Parameter Identification and Model Updating of High-rise Steel Structure
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摘要 广州新电视塔(GNTVT)是一座高度为610m的超高层柔性钢结构,很有必要对其进行健康监测。应用多参考点稳定图算法(M-NExT/ERA)、数据驱动随机子空间识别法(SSI/Data)和增强频域分解法(EFDD),依据GNTVT Benchmark提供的结构振动数据识别广州新电视塔的模态参数,以掌握其动态特性;利用ANSYS建立GNTVT的有限元模型,根据识别得到的实测模态参数,结合遗传算法对GNTVT初始有限元模型进行参数修正,使有限元模型得以正确反映真实结构的动态特性,以供后续健康监测研究之用。 Structure health monitoring is very necessary for Guangzhou New TV Tower(NGTVT),which is a 610 meters high high-rise steel structure.This paper applies multiple reference DOFs stabilization diagram algorithm(M-NExT/ERA),Data-Driven Stochastic Subspace Identification(SSI/Data) and Enhanced Frequency Domain Decomposition(EFDD) to the extraction of modal parameters of GNTVT on the basis of acceleration measurements(GNTVT Benchmark).Then Finite Element Model of GNTVT is modeled using GNTVT,at last the modal parameters results are used for the model updating based on Genetic Algorithm of GNTVT EFM model.
出处 《土木建筑与环境工程》 CSCD 北大核心 2013年第S1期57-61,共5页 Journal of Civil,Architectural & Environment Engineering
基金 广东省交通运输厅科技项目(2010-02-015)
关键词 广州新电视塔 模态参数识别 遗传算法 有限元 参数修正 Guangzhou New TV Tower modal parameter identification genetic algorithm finite element model updating
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