计算力学学报2024，Vol.41Issue(4)：641-650,10.DOI:10.7511/jslx20230226001
基于DKF和稀疏约束的激励和响应估计
Excitation and response estimation based on DKF and sparse constraint
摘要
Abstract
To solve the problem of low frequency drift in excitation and response estimation by acceleration measurements,a method of excitation and response estimation based on DKF and sparse constraint is proposed.Firstly,the DKF algorithm is established based on a state-space model to separate the estimation of excitation and state.Secondly,considering the sparsity of excitation and the uncertainty of measurement noise,an inequality-constrained optimization model for excitation estimation is established based on CS.PM technique is used to solve the optimization problem so that the updated excitation is obtained.Finally,the modal superposition method is used to reconstruct various responses.The proposed method is verified by numerical simulation and test of a simply supported beam.The results show that,when acceleration sensors are collocated,the sparse solution of excitation can be obtained by the proposed method.By comparing the time history curve and the spectral diagrams of excitation and displacement,it is found that the low frequency components of the excitation and displacement are effectively suppressed with good robustness to noise,the method can still maintain the sparsity when two excitations are applied.When the acceleration sensors are non-collocated,the complete spatial sparse excitation cannot be estimated,but the unknown responses can still be estimated.关键词
激励和响应估计/DKF算法/压缩感知/伪测量技术Key words
excitation and response estimation/DKF algorithm/compressed sensing/pseudo measurement technique分类
机械制造引用本文复制引用
彭珍瑞,董琪,王启栋..基于DKF和稀疏约束的激励和响应估计[J].计算力学学报,2024,41(4):641-650,10.基金项目
国家自然科学基金(62161018) （62161018）
甘肃省优秀研究生创新之星项目(2022CXZX-520)资助. （2022CXZX-520）
