[1]张肖雄,贺佳,许斌.基于卡尔曼滤波和递推最小二乘在部分观测信息下的参数识别法[J].地震工程与工程振动,2019,39(02):134-140.[doi:10.13197/j.eeev.2019.02.134.zhangxx.014]
 ZHANG Xiaoxiong,HE Jia,XU Bin.Structural parameter identification basing on Kalman filter and recursive least square estimation with limited observations[J].EARTHQUAKE ENGINEERING AND ENGINEERING DYNAMICS,2019,39(02):134-140.[doi:10.13197/j.eeev.2019.02.134.zhangxx.014]
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基于卡尔曼滤波和递推最小二乘在部分观测信息下的参数识别法
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《地震工程与工程振动》[ISSN:/CN:]

卷:
39
期数:
2019年02
页码:
134-140
栏目:
论文
出版日期:
2019-04-30

文章信息/Info

Title:
Structural parameter identification basing on Kalman filter and recursive least square estimation with limited observations
作者:
张肖雄1 贺佳1 许斌2
1. 工程结构损伤诊断湖南省重点实验室, 湖南大学 土木工程学院, 湖南 长沙 410082;
2. 华侨大学 土木工程学院, 福建 厦门 361021
Author(s):
ZHANG Xiaoxiong1 HE Jia1 XU Bin2
1. Hunan Provincial Key Laboratory on Damage Diagnosis for Engineering Structures, College of Civil Engineering, Hunan University, Changsha 410082, China;
2. Huaqiao University, College of Civil Engineering, Xiamen 361021, China
关键词:
参数识别响应估计卡尔曼滤波递推最小二乘法有限观测
Keywords:
parameter identificationresponse estimationKalman filterrecursive least-squares estimationlimited observations
分类号:
TU311.3;TB122
DOI:
10.13197/j.eeev.2019.02.134.zhangxx.014
摘要:
有限观测信息下的参数识别是结构健康监测领域内的一个热点问题,传统的卡尔曼滤波(Kalman Filter,KF)不能识别结构参数,递推最小二乘法(Recursive Least Square Estimation,RLSE)可用于参数识别,但需已知结构全部响应,为此提出一种基于KF和RLSE的参数联合识别法,该方法首先利用部分自由度上的加速度响应观测值,通过KF估计下一步的系统响应信息,包括速度和位移响应;然后,基于该响应估计信息和当前步的结构参数估计值,根据运动平衡方程,获得下一步的加速度响应估计值;最后,利用已观测的有限加速度响应,获得改进的加速度响应向量,进而基于RLSE获得下一步的结构参数识别值。简支梁数值算例结果表明,该方法能准确识别结构参数,同时能实现系统响应的有效估计。
Abstract:
System identification using limited outputs is of importance for structural health monitoring. The traditional Kalman filter (KF) cannot be used for parameters identification. The recursive least-squares estimation (RLSE) can be employed for system identification while the complete structural responses are available. Here, based on KF and RLSE, a structural parameter identification method is proposed. Firstly, the structural states including displacement and velocity responses at the next step are estimated by means of KF using limited acceleration measurements. Then, based on these estimated responses and the structural parameters identified at the current step, the acceleration responses at the next step are estimated by the differential equation of motion. Finally, the updated acceleration responses are obtained using the limited measurements, and the structural parameters at the next step can be identified by means of RLSE. The effectiveness and robustness of the proposed approach is verified via the numerical example of a simply supported beam model. Numerical results show that the proposed approach can accurately identify the structure parameters and structural states.

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备注/Memo

备注/Memo:
收稿日期:2018-9-8;改回日期:2018-12-10。
基金项目:国家自然科学基金青年科学基金项目(51708198);湖南省自然科学基金青年科学基金项目(2018JJ3054)
作者简介:张肖雄(1995-),男,硕士研究生,主要从事结构健康监测及系统识别研究.E-mail:zhangxiaoxiong95@163.com
通讯作者:贺佳(1983-),男,副教授,博士,主要从事结构健康监测及系统识别研究.E-mail:jiahe@hnu.edu.cn
更新日期/Last Update: 1900-01-01