多因素型结构基本自振周期预测模型的研究
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摘要
为获得一种更有效的估算结构基本自振周期的方法,采用SVSA结构振动信号采集分析系统对上海地区287幢房屋的脉动响应进行了现场实测,得到574个结构脉动响应样本及其对应的结构相关信息;针对现场动测结果数据量多、不规律、变化大的特点,采用基于方差分析的特殊统计处理方法对现场动测数据进行分析回归。经方差分析得到对结构基本自振周期影响最大的3个因素为层数、抗侧力体系与结构材料,以层数为主导因素,分别对其余2个因素分类回归经验公式。在确保回归效果显著的前提下,考虑实际应用的简便性,提出了简化的具有双侧95%置信区间的多因素型周期预测模型。
In order to derive a more efficient method for the estimation of a structural fundamental natural period,287 buildings in Shanghai are measured by SVSA to obtain 574 ambient vibration response measurements and the structural information are collected as well.Special statistical approach based on ANOVA(analysis of variance) is applied to analyze and to regress the data for its large quantity,irregularity and variability.According to the results of ANOVA,the number of stories,lateral-force-resisting-system and structural material are the three most significant factors to a fundamental natural period,thus empirical formulas are regressed respectively for the latter two while regarding the number of stories as the key factor.On the premise of the significance of regression effects,simplified multi-factor fundamental period predictive models with two-side 95% confidence intervals are proposed for the convenience in application.
In order to derive a more efficient method for the estimation of a structural fundamental natural period,287 buildings in Shanghai are measured by SVSA to obtain 574 ambient vibration response measurements and the structural information are collected as well.Special statistical approach based on ANOVA(analysis of variance) is applied to analyze and to regress the data for its large quantity,irregularity and variability.According to the results of ANOVA,the number of stories,lateral-force-resisting-system and structural material are the three most significant factors to a fundamental natural period,thus empirical formulas are regressed respectively for the latter two while regarding the number of stories as the key factor.On the premise of the significance of regression effects,simplified multi-factor fundamental period predictive models with two-side 95% confidence intervals are proposed for the convenience in application.
引文
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[2]Trifunac M D.Wind and microtremor induced vibrationsof a 22-story steel frame building[R].Pasadena,California:California Institute of Technology,1970.
[3]Vdadia F E,Trifunac M D.Ambient vibration test offull-scale structure[C].Rome,Italy:5th WorldConference on Earthquake Engineering,1973:1430―1439.
[4]王广军,樊水荣.建筑自振周期经验公式的述评(上)[J].世界地震工程,1989(3):33―42.Wang Guangjun,Fan Shuirong.Comment on empiricalformulas for estimating structural natural periods(A)[J].World Earthquake Engineering,1989(3):33―42.(inChinese)
[5]王广军,樊水荣.建筑自振周期经验公式的述评(下)[J].世界地震工程,1989(4):35―43.Wang Guangjun,Fan Shuirong.Comment on empiricalformulas for estimating structural natural periods(B)[J].World Earthquake Engineering,1989(3):35―43.(inChinese)
[6]王广军,王玉朋,陈德彬.建筑自振周期经验公式一些问题的探讨[J].建筑科学,1990(4):21―27.Wang Guangjun,Wang Yupeng,Chen Debin.A Studyon Some Problems in Empirical Formulas for EstimatingStructural Natural Periods[J].Building Science,1990(4):21―27.(in Chinese)
[7]Goel R K,Chopra A K.Period formulas formoment-resisting frame building[J].Journal ofStructural Engineering,1997,124(4):426―433.
[8]Fritz W P,Jones N P.Predictive models for the medianand variability of building period and damping[J].Journal of Structural Engineering,2009,135(5):576―586.
[9]王勇.结构振动信号的采集与处理方法研究[D].上海:同济大学,2006.Wang Yong.Research on the acquisition and processionof structural vibration signal[D].Shanghai:TongjiUniversity,2006.(in Chinese)
[10]汪洋.钢结构房屋长期微振动观测及模型修正技术研究[D].上海:同济大学,2008.Wang Yang.Research on Libration observation andmodel updating of steel structure[D].Shanghai:TongjiUniversity,2008.(in Chinese)
[11]Chrysanthakopoulos C,Bazeos N,Bekos D E.Approximate formulae for natural periods of plane steelframes[J].Journal of Constructional Steel Research,2006,62(6):592―604.
[12]Devore J L.Probability and statistics for engineering andthe sciences[M].Beijing:China Machine Press,2005:410―436.
[13]同济大学概率统计教研组.概率统计[M].上海:同济大学出版社,2004:182―262.Research Group of Probability and Statistics in TongjiUniversity.Probability and Statistics[M].Shanghai:Tongji University Press,2004:180―262.(in Chinese)
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