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新型随机地震动模型
引用本文:曾珂,牛荻涛,商瑞霞.新型随机地震动模型[J].地震工程与工程振动,2005,25(6):30-37.
作者姓名:曾珂  牛荻涛  商瑞霞
作者单位:1. 西安建筑科技大学,土木工程学院,陕西,西安,710055
2. 中国建筑技术集团有限公司,北京,100013
基金项目:国家自然科学基金项目(50078044)
摘    要:在研究结构的随机地震反应时,要用大量的符合场地条件的地震记录作为输入数据。但强震历史记录却不是每个地区都有的,因此根据符合场地条件的现有地震记录建立随机地震动模型具有重要意义。本文利用中国抗震规范2001版修正选取的样本波作为目标波,考虑了幅值和频率的双重非平稳性,建立了新型随机地震动模型——改进的时变ARMA模型随机地震动模型。通过使用残差的卡方检验法,对多种非平稳ARMA模型生成的模拟波进行检验;同时又比较丁模拟波与目标波的功率谱密度图和反应谱图。结果证明:此法能够更精确地反映不同场地条件地震动的频谱和幅值的真实内容,从而建立符合目标场地条件的更为有效的模拟地震动,为相关研究与工程设计架起一座桥梁。

关 键 词:时变ARMA模型  Box-Cox变换  非平稳随机地震动模型
文章编号:1000-1301(2005)06-0030-08
收稿时间:2004-11-15
修稿时间:2004-11-152005-04-20

New stochastic seismic model
Zeng Ke,Niu Di-tao,Shang Rui-xia.New stochastic seismic model[J].Earthquake Engineering and Engineering Vibration,2005,25(6):30-37.
Authors:Zeng Ke  Niu Di-tao  Shang Rui-xia
Abstract:When the stochastic seismic response of the structures is studied,lots of the earthquake records fit for the selected site are necessary to be used for initial data for structure model analysis.In the given site it always hasn't the strong earthquake records,thus it's very significant to make satisfactory model used to describe realistic earthquake ground motion time history matching the location condition.In this paper,using the sample records reformed by Chinese code 2001 version for seismic design of buildings as target earthquake records,the modified discrete time-varying ARMA model is made.Both amplitude and frequency nonstationarities are incorporated in the model.Chi-Square verification tests are performed in the different nonstationary ARMA model.Applications of these verification procedures are given and show that the proposed models are able to reflect accurately the nonstationary features of real earthquake accelerogram,including both the time-variation of the frequency and amplitude content.Thus the more efficiently simulated earthquake records matching the site's condition are made.It sets up a bridge from the research to civil engineering design.
Keywords:time vary ARMA model  Box-Cox transform  nonstationarity stochastic seismic model
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