基于不完整正弦基础激励响应数据的模型修正方法

文章直接应用航天器正弦振动试验所获取的结构动力学特性响应数据，开展了模型修正方法的研究。在试验数据不完整时，需进行模型缩聚。首先对比分析了Guyan缩聚和IRS缩聚方法的优缺点和适用范围；然后以缩聚后模型为基础，推导了基于基础激励响应数据的模型修正方法；最后以GARTEUR桁架结构的不完整的基础激励试验数据为基础对归一化的结构参数进行修正。结果表明:IRS缩聚模型修正后对模态频率具有良好的复现能力和预示能力，对响应曲线的修正也得到了明显改善。

Model updating method based on imperfect sine vibration test response data

The spacecraft sine vibration test can be used to reveal multiform dynamic characteristics, so a model updating method based on the sine vibration response data is important. The model reduction is necessary in an incomplete test data process. Firstly, the Guyan reduction method and the IRS reduction method are compared to show their merit/defect and application range. Secondly, an updating method based on excitation response data is derived by using the reduced model. Lastly, the unitary non-updated parameters are updated based on the incomplete test data of the GARTEUR. The results show that the IRS reduced updated model performs good in calculating/predicting the modes in/outside the updating frequency range with favorable results of response updating.