An algorithm for correcting structure model parameters based on a frequency response function

Abstract

The invention relates to an algorithm for correcting structure model parameters based on a frequency response function, which comprises the following steps of: acquiring time history data and time history response data, and introducing a multivariate circle symmetry proportion distribution theorem to derive and obtain a probability density function and a covariance matrix of the actually measuredfrequency response function; Introducing a prediction error and a to-be-corrected parameter to obtain a covariance matrix containing the to-be-corrected parameter; Obtaining a probability density function of a frequency response function under the action of single-point excitation according to the determinant and the inverse theorem of the matrix; Obtaining a maximum likelihood function expressedin a form of a maximum likelihood function and a logarithm maximum likelihood function according to a maximum likelihood principle; Obtaining a posterior probability density function of the random variable according to the Bayesian theorem; And expressing the posterior probability density function as a logarithm likelihood function form, so that an objective function is obtained. The uncertainty of the correction parameters is quantized, the calculation precision of the correction parameters is improved, and the correction of the structure finite element model is realized.

Description

technical field [0001] The invention belongs to the field of structural model correction, and in particular relates to an algorithm 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 correc...

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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