Identification of Multi-Point Dynamic Load Positions Based on Filter Coefficient Method

Dynamic load identification plays an important role in practical engineering. In this paper, a novel fast algorithm is investigated to identify the multi-point dynamic load positions in frequency domain. For any given frequency, the amplitude of each load spectrum is relatively constant. By solving the kinetic equation set with the elimination method, the relationship of the true dynamic load positions can be expressed as the form of filter coefficients, then many dynamic load position combinations can be found that they do not satisfy the relationship so they can be excluded from the possible true position combinations. Compared to the traditional method, the novel algorithm only needs to sort out the true positions from a few dynamic load position combinations by the minimum determination coefficient method, which reduces the number of matrix inversion operations and improves the speed of the identification of load positions. Through a numerical simulation and an identification test on the simply supported beam structure, the high accuracy and effectiveness of the novel algorithm are successfully demonstrated, while the rapidity of the novel algorithm is shown by comparing the computation time of the novel algorithm with that of the traditional method.

[1]  Per Christian Hansen,et al.  Truncated Singular Value Decomposition Solutions to Discrete Ill-Posed Problems with Ill-Determined Numerical Rank , 1990, SIAM J. Sci. Comput..

[2]  Xinqun Zhu,et al.  Moving load identification on a simply supported orthotropic plate , 2007 .

[3]  M. Ekstrom,et al.  On the Application of Eigenvector Expansions to Numerical Deconvolution , 1974 .

[4]  F. D. Bartlett,et al.  Model Verification of Force Determination for Measuring Vibratory Loads , 1979 .

[5]  Zhu De-chu Time-domain identification technology for dynamic load locations , 2013 .

[6]  Tommy H.T. Chan,et al.  Moving Force Identification based on the Frequency-Time Domain Method , 2003 .

[7]  Yi Liu,et al.  Dynamic force identification based on enhanced least squares and total least-squares schemes in the frequency domain , 2005 .

[8]  D. Thompson,et al.  Comparison of methods for parameter selection in Tikhonov regularization with application to inverse force determination , 2007 .

[9]  Stefan Hurlebaus,et al.  IDENTIFICATION OF THE IMPACT LOCATION ON A PLATE USING WAVELETS , 1998 .

[10]  C. Jiang,et al.  A novel computational inverse technique for load identification using the shape function method of moving least square fitting , 2014 .

[11]  Siu-Seong Law,et al.  Moving force identification using an existing prestressed concrete bridge , 2000 .

[12]  Qiuhai Lu,et al.  Impact localization and identification under a constrained optimization scheme , 2016 .

[13]  Claus-Peter Fritzen,et al.  Impact identification and localization using a sample-force-dictionary - General Theory and its applications to beam structures , 2016 .

[14]  Per Christian Hansen,et al.  The Modified Truncated SVD Method for Regularization in General Form , 1992, SIAM J. Sci. Comput..

[15]  Per Christian Hansen,et al.  Regularization methods for large-scale problems , 1993 .

[16]  Jiang Jinhui Identification technology of dynamic load location , 2012 .

[17]  Abdellatif Khamlichi,et al.  Assessing impact force localization by using a particle swarm optimization algorithm , 2014 .

[18]  Xu Han,et al.  Time‐domain Galerkin method for dynamic load identification , 2016 .