Station structure model correction analysis method and system

Abstract

The invention belongs to the field of finite element analysis, and particularly provides a station structure model correction analysis method and system; wherein the method comprises the steps: S1, building a finite element model for a station structure, and appointing an interested unit in the finite element model as a design variable; s2, selecting interested units from each part, processing the units with the same materials as super-units, increasing and contributing a design variable to each super-unit, and endowing an elastic modulus to the material property of each design variable; s3, carrying out sensitivity analysis on each super unit to obtain a Spearman grade correlation coefficient; s4, comparing the absolute value of the Spearman grade correlation coefficient of each super-unit with a preset value to delete unqualified design variables; s5, carrying out optimization analysis on the screened model to obtain an optimized and corrected model. By performing secondary development and parametric modeling on large finite element analysis software and utilizing an optimization module, model correction is realized, and the data analysis precision of subsequent models is improved.

Description

technical field [0001] The invention relates to the field of finite element analysis, and more specifically, to a method and system for revising and analyzing a station structure model. Background technique [0002] Structural health monitoring is widely used in aerospace, civil engineering and bridge safety. However, when health monitoring is applied to life assessment of large-scale station structures, the following problems make the assessment results inaccurate: [0003] (1) The measurement information is incomplete. Due to insufficient frequency and modal information obtained from measurements, the results of model correction are not unique. For example, when modifying the stiffness of a unit, if the measured frequency and the number of modes are far less than the number of units, it is impossible to uniquely determine the modification parameters of the stiffness. The resulting model is not unique and therefore cannot accurately predict structural life. [0004] (2)...

AI Technical Summary

Problems solved by technology

Due to insufficient frequency and modal information obtained from measurements, the results of model correction are not unique

For example, when modifying the stiffness of a unit, if the measured frequency and the number of modes are far less than the number of units, it is impossible to uniquely determine the modification parameters of the stiffness

The resulting model is not unique and therefore cannot accurately predict structural life

[0004] (2) Lack of high-order modes

However, the relationship between stress and high-order modes is relatively large, so the estimation of stress may be inaccurate, so it is difficult to obtain accurate results when using stress to estimate the life of a structure

[0005] (3) The damage index is not sensitive enough to effectively distinguish whether there is an abnormality in the structure

[0006] Therefore, when analyzing the life of a structure, the traditional modeling has a lot of defects, and the model analysis with defects can no longer meet the actual engineering needs

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