模型缩聚-模型修正迭代方法的研究

模型修正中通常需要解决自由度匹配问题，模型缩聚是解决这一问题的一种方法。当有限元建模误差较大时，模型缩聚的近似会大大降低模型修正的精度。针对这一问题，提出了模型缩聚-模型修正迭代方法，消除模型缩聚带来的误差。文中应用IRS缩聚和基于频响函数的模型修正方法对提出的迭代方法进行了具体讨论。通过板梁混合结构的数值模拟实验，比较了现有修正方法和迭代修正方法的修正精度。结果表明提出的迭代方法有效提高了修正精度，使修正后的模型频率和物理参数更逼近真实值。同时该方法具有较高的迭代收敛效率，符合实际工程应用的要求。

Research on the iterative method for model reduction-model updating

In order to solve the problem of low accuracy of model updating due to unmatched degrees of freedom,an iterative method for model reduction-model updating was proposed to dispel the error caused by model reduction. The method of IRS model reduction and model updating based on frequency response function (FRF),which is used in the iterative method,was discussed. The updating accuracy of the current method was compared with that of the iterative method by a numerical example of beam-plane structure. The result shows that the iterative method can increase the updating accuracy successfully and make the frequencies and other physical parameters in finite element model closer to those of the real structure. In addition,the method has high efficiency of iteration,which makes it meet the need of real engineering application.