基于子结构的非线性参数系统动力反演方法研究  

Nonlinear system parameters inversion method based on substructure

作　　者：林湘[1] 吴子燕[1] 邓子辰[1,2] 

机构地区：[1]西北工业大学力学与土木建筑学院,西安710072 [2]大连理工大学工业装备结构分析国家重点实验室,大连116023

出　　处：《计算力学学报》2009年第1期15-19,共5页Chinese Journal of Computational Mechanics

基　　金：国家高技术研究发展计划(863计划)资助项目(2006AA04Z437);国家自然科学基金(10632030);教育部新世纪优秀人才计划(NCET-04-0958);大连理工大学工业装备结构分析国家重点实验室开放基金资助项目

摘　　要：研究了输入、输出不完备情况下的非线性参数系统动力反演问题。将子结构技术与分解算法相结合,引入广义逆,无需迭代,直接求得待识别参数的极小范数最小二乘解,反演获得未知输入荷载。本文从理论上论证了该方法的收敛性和严格的适用条件,为有限测点条件下非线性参数系统的动力反演问题提供了一个较好的解决方法。与全量补偿算法相比,计算效率大大提高,具有广泛的工程实际应用前景。数值算例表明该方法具有很好的参数识别精度及荷载反演效果。The nonlinear system parameter identification problem with incomplete input and output information is studied. The consideration of Rayleigh-type proportional damping introduces a nonlinear system parameters identification problem. In this paper, combined with decomposition algorithm, the proposed method obtains minimal norm least square solution of the unknown system parameter and the unknown input in one step by using Moore-Penrose Pseudo-inverse. The substructure method offers an efficient approach for the dynamic detection of engineering structures with limited observations. Compared with Compensation Method, the method is more efficient and has a wider application background. The numerical example shows that the proposed approach can effectively identify the structural parameters from incomplete measurements. The algorithm is expected to provide an economical, simple, efficient,and robust system identification technique that can be used as a nondestructive defect detection procedure in the future.

关 键 词：动力反演 非线性参数识别 广义逆 子结构 

分 类 号：TU311.3[建筑科学—结构工程]