摘要
针对结构特性参数识别问题,提出了一种基于Galerkin映射-减基法的参数反求方法。采用该方法对结构进行有限元建模,在观测点位置通过对向量子空间的夹角进行评判,构造出非奇异的观测点基矩阵及相应的整体基矩阵。通过使向量离散L2范数最小化途径构建结构参数的减基识别模型,进而利用信赖域优化技术求解得出问题的结构参数。算例表明,该方法在反求精度和总体计算效率方面优于传统方法。
An effective parameter identification technique which was based on the Galerkin map-ping-reduced basis method was proposed for dealing with parameterized structural problems .The in-vestigated structure was firstly discretized by the finite element method .And then using the angle of vector subspace ,the nonsingular monitoring basis matrix and corresponding whole basis matrix were constructed in the positions of monitoring points .Subsequently ,the identification model of structural parameters in the reduced basis model was constructed by minimizing discrete L2 norm of vector .Fi-nally ,the parameters of original problem were identified using the corresponding trust region optimi-zation technique .An example herein demonstrates the presented method has higher computational ac-curacy and total efficiency than that of the existing classical methods .
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2014年第14期1951-1955,共5页
China Mechanical Engineering
基金
国家自然科学基金资助项目(11202076)
吉首大学校级科研项目(jsdxrcyjkyxm201209)
关键词
减基法
参数反求
Galerkin映射
非奇异
信赖域
reduced basis method
parameter identification
Galerkin mapping
nonsingular
trust region