基于Vector Random Decrement技术和特征系统实现算法ERA的模态参数识别

Modal parameter identification based on vector random decrement technique and eigensystem realization algorithms ERA

现代的大型复杂结构,如大坝、高层建筑、桥梁及海洋平台等,处于复杂的环境载荷作用下,这些环境载荷往往是无法测量的。在仅有输出响应时,应用随机减量法RDT获得自由衰减响应信号,而后用时域复指数拟合法、ITD法、特征系统实现算法ERA等算法获得结构的模态参数是一种有效的方法。但在数据量有限时,随机减量函数的平均次数过少,导致RD函数的收敛性较差。为此提出了利用Vector Random Decrement技术(VRDT)提取自由衰减响应信号,而后利用特征系统实现算法ERA求得模态参数的方法,新算法能够有效地提高模态参数识别精度。数值算例验证了所提算法的有效性。

Modern large-scale complex structures such as dams,highrise buildings,bridges and offshore platforms etc,are in a complex environment,where environmental load is can not measured usually.When getting the output response only,the random decrement technique RDT can be used to get the free decay response signal.After that it is an effective method to obtain the modal parameters of the structure using the time-domain complex exponential fitting,the ITD method and the eigensystem realization algorithm ERA from the free decay response signal.However,with the limited amount of data,average numbers of the random decrement function is too small to lead the RD function converge.This paper proposes the vector random decrement technology （VRDT） to extract the free decay response signal,and then using the eigensystem realization algorithm ERA to get modal parameters.This new algorithm can effectively improve the precision of modal parameter identification.The numerical examples verify the effectiveness of the proposed algorithm.