Modified truncated singular value decomposition method for moving force identification
Zhen Chen, Lu Deng, Xuan Kong
Abstract
In this study, a modified truncated singular value decomposition (MTSVD) method is proposed for the identification of dynamic moving forces on simply-supported beams. By regularizing the truncated singular value decomposition (TSVD) method, the MTSVD method focuses on overcoming the ill-posed problems that intrinsically exist in moving force identification. Two regularization parameters, namely, regularization matrix and truncating point are the most important regularization parameters affecting the performance of the MTSVD method. The accuracy and efficiency of the MTSVD method is shown by comparing the results with the conventional counterpart SVD and TSVD methods. In addition, the proposed method is also compared with a similar method recently proposed by the author, that is, the piecewise polynomial truncated singular value decomposition (PP-TSVD) method. Numerical simulations demonstrate that the performance of the MTSVD method is significantly improved compared with the PP-TSVD method in high noise level cases.