A Method of Modifying Structural Model Parameters Based on Frequency Response Function

Abstract

The invention relates to a method for revising structural model parameters based on a frequency response function, comprising the following steps: collecting time history data and time history response data, introducing the multivariate circular symmetric proportional distribution theorem to derive the probability density function and covariance of the measured frequency response function Matrix; introduce the prediction error and the parameters to be corrected to obtain the covariance matrix containing the parameters to be corrected; according to the determinant of the matrix and the inversion theorem, the probability density function of the frequency response function under single-point excitation is obtained; according to the maximum likelihood principle, The maximum likelihood function expressed in the form of the maximum likelihood function and the logarithmic maximum likelihood function is obtained; according to Bayes' theorem, the posterior probability density function of the random variable is obtained; the posterior probability density function is then expressed as a logarithm The form of the likelihood function is to obtain the objective function. The invention quantifies the uncertainty of the correction parameters, improves the calculation accuracy of the correction parameters, and realizes the correction of the structure finite element model.

Description

technical field [0001] The invention belongs to the field of structural model correction, and in particular relates to a method for correcting structural model parameters based on a frequency response function. Background technique [0002] In civil engineering, machinery, vehicles and other scientific fields, finite element technology is often used to construct accurate and reasonable numerical models. However, due to the unavoidable effects of modeling errors, structural variations, and test variations, the results obtained through finite element numerical analysis do not agree well with the data obtained from experimental observations. The finite element model correction technology is to use the measured data of the system to correct the model parameters, so that the revised finite element model can reflect and predict the behavior of the system more accurately, and lay the foundation for future structural health monitoring and damage identification. The model correction...

AI Technical Summary

Problems solved by technology

Even if the various uncertainties mentioned above are small, the coupling together may cause a large deviation in the structural response, and the influence of uncertain factors will overwhelm or even cover up the real information of the structural response, so that wrong conclusions can be drawn

Therefore, it is difficult to fundamentally grasp the discrete behavior of structural model correction parameters by fully adopting deterministic analysis methods. In addition, deterministic methods also have non-negligible limitations in accurately describing system characteristics and profoundly revealing the objective laws of an uncertain world.

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