Modification Method of Interval Model Based on Taylor Series Expansion

Abstract

The invention relates to an interval model correcting method based on Taylor series expansion. The method includes: building function correspondence of structural response interval mid-value and radius and structural parameter interval mid-value and radius to serve as the theoretical foundation of interval model correction; using deterministic model correction to correct structural parameter interval mid-value according to actually measured response interval mid-value; in order to simplify calculation, using a difference method to calculate structural parameter partial derivative at the corrected interval mid-value so as to obtain an approximate expression of function correspondence of interval radius; using deterministic model correction to perform iteration optimization according to actually measured response interval radius and on the basis of the obtained approximate expression so as to correct structural parameter interval radius. The method is clear in theoretical foundation, simple in optimization, practical, and high in interval parameter correction precision.

Description

technical field [0001] The invention relates to the technical field of finite element model correction, in particular to an interval model correction method based on Taylor series expansion. Background technique [0002] Finite element model correction technology has been widely used in aerospace, civil, mechanical and other engineering fields. However, traditional model updating methods are based on the assumption of parameter determinism. Uncertainty factors in actual engineering structures are ubiquitous and unavoidable, such as material discreteness, measurement errors, manufacturing errors, etc., which lead to uncertainties in structural parameters. If the deterministic theory and method are still used to correct the finite element model, it will inevitably lead to unreliable correction results, which are quite different from the actual situation. Therefore, the stochastic model correction method that considers the parameter uncertainty has been favored by many researc...

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Problems solved by technology

For actual engineering structures, it is often difficult to satisfy the above conditions at the same time. At the same time, when the output response contains the eigenvector of the system, or the overall mass and stiffness matrix of the structure are nonlinear functions of the correction parameters, the vertex method is prone to failure

At the same time, although the global optimization algorithm has global search capabilities, the algorithm combined with interval analysis is often more complex, and the optimization result may still fall into a local optimal value, resulting in the predicted parameter interval being not necessarily accurate.

At the same time, if the interval correction problem involves many parameters, the algorithm requires a large number of iterative calculations, which will consume a large amount of calculation costs

In addition, it is generally more complicated to solve the corresponding model correction problems within the probabilistic or non-probability framework. If the problem can be solved within the deterministic framework as much as possible, it will greatly benefit the simplification of the correction problem and improve the computational efficiency. Therefore, it is necessary to study this

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