摘要
研究了输入、输出信息皆不完备情况下的结构参数识别以及荷载反演问题。阐述了一种通用的子结构动力方程及其参数识别方程建立的基本原理和方法,并针对实际工程检测中子结构参数识别方程的输入特性,分别采用一种与之相适应的分解反演算法或统计平均算法。子结构技术与分解算法或统计平均算法的有效结合,为有限测点条件下的结构参数识别及荷载反演问题提供了一个较好的解决方案。大量的数值计算结果表明,本文提出的方法具有很好的参数识别精度及荷载反演效果。
The structural system identification with incomplete input and output information is studied. The substructural dynamic equations and parameter identification equations are established, which can be applied to various structures. According to the property of input information in substructures, a decomposition algorithm or a statistical average algorithm is used. The two algorithms identify the structural parameters effectively even when the excitations of part degrees of freedom or seismic excitations are unknown. Combined with decomposition algorithm or statistical average algorithm, the substructure method proposed in this paper offers an efficient approach for the dynamic detection of engineering structures with limited observations. For verification purpose, both the noise-free and noise-included output responses are considered in the numerical examples. Results show that the structural parameters and loads can be identified robustly in all cases.
出处
《工程力学》
EI
CSCD
北大核心
2005年第5期94-98,共5页
Engineering Mechanics
基金
湖南省自然科学基金资助项目(04JJ40060)
关键词
子结构
参数识别
荷载反演
时域
算法
substructure
parameter identification
load inversion
time domain
algorithm
