A new iteration regularization method for dynamic load identification of stochastic structures. (July 2021) - Wang, Linjun; Peng, Yunlong; Xie, Youxiang; Chen, Baojia; Du, Yixian
Highlights: A new iteration regularization algorithm is proposed. The proposed iteration regularization algorithm is strictly proved. The present method is powerful for load identification for stochastic structure. The newly developed method saves computational cost remarkably compared with MCS. Numerical simulations validate the obtained theoretical results. Abstract: In this paper, we propose a novel fast convergence iterative regularization method on the basis of a new iterative regularization operator to solve the dynamic load identification of stochastic structures. Firstly, the validity and convergence of the proposed algorithm is proved by strict mathematical theory and numerical results of engineering example. Secondly, the dynamic load identification of uncertain structures can be transformed into a series of deterministic inverse problems by the matrix perturbation method. Finally, we also assess the statistical characteristics of identified loads using the statistical theory. Particularly, the proposed method successfully solves the dynamic load identification of stochastic structure. Numerical simulations are given to validate the feasibility of the presented method in this paper.