环境激励下剪切型结构层间刚度识别的新方法
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摘要
研究环境激励下剪切型结构的层间刚度识别问题,提出了一种新的解决方法.该方法采用自然激励技术实现结构随机响应向确定性响应的过渡;推演了剪切型结构自由振动的参数解耦方程,简化了识别过程、降低了计算量.将自然激励技术、参数解耦方法和扩展卡尔曼滤波算法三者有效结合,为环境激励下剪切型结构的刚度识别提供了一个较好的解决方案.以一个6自由度剪切型结构为例,对该方法进行了数值模拟,结果表明:该方法能比较准确地识别结构层间刚度,可用于剪切型结构健康监测的实际工程.
Inter-story stiffness identification of shearing structures under ambient excitation was studied and a new method was presented.In the method,the transition from structural random response to deterministic response was realized by the natural excitation technique(NExT).The parameter-decoupled free vibration equation of shearing structures was deduced,and the equation could simplify the process of identification and reduce the amount of calculation.Through the effective combination of the NExT,the parameter-decoupled method and the extended Kalman filter(EKF) algorithm,a good scheme was presented for inter-story stiffness identification of shearing structures under ambient excitation.Using a shearing structure with six-degree-of-freedom as example,the scheme was tested by numerical simulation.The results show that the inter-story stiffness can be identified basically with accuracy,and the scheme can be applied in practical projects for health monitoring of shearing structures.
Inter-story stiffness identification of shearing structures under ambient excitation was studied and a new method was presented.In the method,the transition from structural random response to deterministic response was realized by the natural excitation technique(NExT).The parameter-decoupled free vibration equation of shearing structures was deduced,and the equation could simplify the process of identification and reduce the amount of calculation.Through the effective combination of the NExT,the parameter-decoupled method and the extended Kalman filter(EKF) algorithm,a good scheme was presented for inter-story stiffness identification of shearing structures under ambient excitation.Using a shearing structure with six-degree-of-freedom as example,the scheme was tested by numerical simulation.The results show that the inter-story stiffness can be identified basically with accuracy,and the scheme can be applied in practical projects for health monitoring of shearing structures.
引文
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[2]谢献忠,易伟建.结构物理参数时域识别的子结构方法研究[J].工程力学,2005,22(5):94-98.XIE Xian-zhong,YI Wei-jian.A substructure method for parameter estimation in time domain[J].Engineering Mechanics,2005,22(5):94-98.(in Chinese)
[3]樊素英,李忠献.桥梁结构物理参数识别的双单元子结构法[J].工程力学,2007,24(6):68-72.FAN Su-ying,LI Zhong-xian.A double-element substructure method for physical parameter identification of bridge structures[J].Engineering Mechanics,2007,24(6):68-72.(in Chinese)
[4]JUAN M C,SHIRLEY J D,ERIK A J.Natural excitation technique and eigensystem realization algorithm for phaseⅠof theIASC-ASCE benchmark problem:simulated data[J].Journal of Engineering Mechanics,2004,130(1):49-60.
[5]王树青,李华军.利用消去刚度法进行剪切型系统物理参数识别[J].中国海洋大学学报,2004,34(6):1085-1089.WANG Shu-qing,LI Hua-jun.Stiffness elimination algorithm for physical parameters identification of shearing structures[J].Periodical of Ocean University of China,2004,34(6):1085-1089.(in Chinese)
[6]易伟建,周云.基于高阶局部模态的弹性地基上框架结构物理参数识别研究[J].地震工程与工程振动,2007,27(1):117-124.YI Wei-jian,ZHOU Yun.Research on physical parameter identification of concrete frame structure on elastic foundationbased on higher modes[J].Journal of Earthquake Engineering and Engineering Vibration,2007,27(1):117-124.(inChinese)
[7]JAMES G H,CARNE T G,LAUFFER J P.The natural excitation technique for modal parameter extraction from operatingwind turbines[R].Sandia:Sandia National Laboratories,1993.
[8]BECK J L,VANIK M W,KATAFYGIOTIS L S.Determination of model parameters from ambient vibration data forstructural health monitoring[C]∥Proc,1st World Conf on Structural Control,Pasadena,Calif:[s.n.],1994:3-12.
[9]宝志雯,史文月.基于推广卡尔曼滤波算法的结构模型的参数识别[J].振动与冲击,1990,(1):11-21.BAO Zhi-wen,SHI Wen-yue.Parameter identification of structural models by means of extended kalmanifilter algorithm[J].Vibration and Shock,1990,(1):11-21.(in Chinese)
[10]李国强,李杰.工程结构动力检测理论与应用[M].北京:科学出版社,2002:153-159.
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