| 结构动力模型修正方法研究进展 |
| |
| 引用本文： | 李辉,丁桦.结构动力模型修正方法研究进展[J].力学进展,2005,35(2):170-180. |
| |
| 作者姓名： | 李辉 丁桦 |
| |
| 作者单位： | 中国科学院力学研究所 |
| |
| 基金项目： | 中国海洋石油总公司与中国科学院技术合作项目“海上平台优化设计与关键技术研究”(KJCX23-SW-L03-01)资助项目~~ |
| |
| 摘 要： | 叙述了结构动力模型修正方法的一般原理及与其密切相关的模型缩聚和模态扩展方法,
并且挑选其中具有代表性的文献, 介绍和比较了3种主要的修正方法, 即传统的动力模型修
正方法, 包括矩阵型修正方法和参数型修正方法, 和最近兴起的基于神经网络的模型修正方
法, 重点分析了这些方法的优点和不足之处, 力图能使读者对于这一研究领域的发展有一个
脉络清晰的了解. 最后, 就目前研究中尚未解决的问题作了一些探讨.
|
| 关 键 词： | 模型修正 模型缩聚 模态扩展 特征灵敏度 神经网络 |
PROGRESS IN MODEL UPDATING FOR STRUCTURAL DYNAMICS |
| |
| LI Hui,DING Hua.PROGRESS IN MODEL UPDATING FOR STRUCTURAL DYNAMICS[J].Advances in Mechanics,2005,35(2):170-180. |
| |
| Authors: | LI Hui DING Hua |
| |
| Affiliation: | LI Hui DING Hua Institute of Mechanics,Chinese Academy of Sciences,Beijing 100080,China |
| |
| Abstract: | This paper gives a brief introduction of the general principle of model updating as well as the methods of model reduction and modal expansion closely related to model updating. Some representative references are singled out and introduced with particular attention to three kinds of primary methods of model updating, namely, direct method and parametric method, which are known as traditional methods, and updating method with neural networks. Emphases are put on their merits in application and corresponding disadvantages. Finally, some recent unresolved problems are discussed. |
| |
| Keywords: | model updating model reduction modal expansion eigensensitivity neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《力学进展》浏览原始摘要信息 |
|
点击此处可从《力学进展》下载全文 |
|
