Dynamic load identification for stochastic structures based on Gegenbauer polynomial approximation and regularization method

被引:167
作者
Liu, Jie [1 ]
Sun, Xingsheng [1 ]
Han, Xu [1 ]
Jiang, Chao [1 ]
Yu, Dejie [1 ]
机构
[1] Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金; 国家教育部博士点专项基金资助;
关键词
Load identification; Stochastic structures; lambda-PDF; Gegenbauer polynomials; Orthogonal polynomial expansion; Regularization; BORNE TRANSMISSION PATHS; RESPONSE VARIABILITY; FORCE IDENTIFICATION; OPTIMIZATION METHOD; INTERVAL-ANALYSIS; FINITE-ELEMENTS; INVERSE METHODS; SIMULATION; VIBRATION; QUANTIFICATION;
D O I
10.1016/j.ymssp.2014.10.008
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Based on the Gegenbauer polynomial expansion theory and regularization method, an analytical method is proposed to identify dynamic loads acting on stochastic structures. Dynamic loads are expressed as functions of time and random parameters in time domain and the forward model of dynamic load identification is established through the discretized convolution integral of loads and the corresponding unit-pulse response functions of system. Random parameters are approximated through the random variables with lambda-probability density function (PDFs) or their derivative PDFs. For this kind of random variables, Gegenbauer polynomial expansion is the unique correct choice to transform the problem of load identification for a stochastic structure into its equivalent deterministic system. Just via its equivalent deterministic system, the load identification problem of a stochastic structure can be solved by any available deterministic methods. With measured responses containing noise, the improved regularization operator is adopted to overcome the ill-posedness of load reconstruction and to obtain the stable and approximate solutions of certain inverse problems and the valid assessments of the statistics of identified loads. Numerical simulations demonstrate that with regard to stochastic structures, the identification and assessment of dynamic loads are achieved steadily and effectively by the presented method. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:35 / 54
页数:20
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