摘要
地震激励和结构状态的准确信息是进行结构地震安全性评价和振动控制的前提.当不测量结构的地震激励时,地震激励的识别可作为逆问题,依据测量的结构响应来判断地震激励.尽管已经发展了一些相关的识别方法,但现有方法仍存在一定的局限性或缺陷.为了避免这些问题,该文提出了一种基于未知输入的广义卡尔曼滤波(GKF-UI)多层剪切框架的地震激励的广义识别算法.当不测量结构受到的地震作用时,结构健康监测(SHM)系统测量的数据是结构的绝对响应,因此,结构运动方程的推导建立在绝对坐标系下,其中未知地震激励作为未知外力作用于结构上.该算法可在不观测未知外力作用处的结构绝对加速度响应的情况下,识别结构状态和未知地震激励.提出的GKF-UI的推导基于经典卡尔曼滤波器(KF),但在结构加速度传感器的部署中,它比现有的基于未知输入的卡尔曼滤波器(KF-UI)的荷载辨识方法更具有普遍适用性.通过数值算例中一个6层剪切框架的地震激励识别,验证了该算法的有效性.
The exact information of seismic excitation and structural state is a prerequisite for structural seismic safety assessment and vibration control.When the seismic excitation to a structure is not measured,the seismic excitation can be identified as an inverse problem from measured structural responses.Although some relevant approaches have been developed,the existing appriaches still have certain limitations or drawbacks.To circumvent these problems,a generalized algorithm base on a generalized kalman filtering under unknow input(GKF-UI)are proposed for the identification of seismic excitation to shear frame.When the seismic excitation to a structure is not measured,data measured by an structural health monitoring system are structural absolute responses.Therefore,the structural motion equation in the absolute co-ordinate system is derived,and the unknown seismic excitation is treated as unknown external force acting on the structure.The algorithm can identifies of structural state and unknown seismic excitation without the observation of structural absolute acceleration responses at the location of unknown external force.The derivation of the proposed GKF-UI is based on the classical Kalman filter(KF),but is more general than the existing identification approaches based on KF with unknown input(KF-UI)in the deployments of accelerometers in the building structure.To demonstrate the proposed algorithm,we investigate a numerical example that identifies the seismic excitations to a six-story shear building.
作者
饶勇平
黄金山
邱昊
雷鹰
RAO Yongping;HUANG Jinshan;QIU Hao;LEI Ying(School of Architecture and Civil Engineering,Xiamen University,Xiamen 361005,China)
出处
《厦门大学学报（自然科学版）》
CAS
CSCD
北大核心
2020年第4期578-582,共5页
Journal of Xiamen University：Natural Science
基金
国家自然科学基金(51678509)。
关键词
未知地震激励
荷载识别
卡尔曼滤波
绝对加速度
unknown seismic excitation
load identification
Kalman filter
absolute acceleration
