首页> 外文OA文献 >FEM modeling method of damage structures for structural damage detection
【2h】

FEM modeling method of damage structures for structural damage detection

机译:用于结构损伤检测的损伤结构有限元建模方法

摘要

Many current methods on structural damage identification such as GA algorithms and neural networks technology are often implemented based on a few measured data and a large number of simulation data from structural vibration responses. Therefore, to establish an accurate and efficient dynamics model for a structure with different damage is an important precondition, so that plentiful simulation data of structural vibration response can be acquired using the dynamics model of the structure with damage. There are two problems when directly meshing small structural damage in FEM modeling, i.e., excessive gridding number and unavoidable errors from differently meshing for the same damaged structure. In order to solve these two problems, this paper presents an improved modeling method based on modifying element stiffness matrix at structural damage position using a modification coefficient. The first step of this improved modeling method is to determine modification coefficient of element stiffness matrix based on the coherence of natural frequencies for two kinds of models, and the second step is to verify the coherence of the frequency-response functions. This study also introduces algorithm and calculating results of damaged element stiffness matrix. Influence of structural damage position and constraint conditions on the modification coefficient for small structural damage are also discussed.
机译:基于结构振动响应的一些实测数据和大量仿真数据,经常采用许多当前的结构损伤识别方法,例如GA算法和神经网络技术。因此,建立具有不同损伤程度的结构的准确有效的动力学模型是重要的前提,因此利用具有损伤的结构的动力学模型可以获得大量的结构振动响应仿真数据。在有限元模型中直接对较小的结构损伤进行网格划分时,存在两个问题,即网格数量过多和由于相同的受损结构而导致的不同网格划分不可避免的误差。为了解决这两个问题,本文提出了一种改进的建模方法,该方法基于使用修正系数修正结构损伤位置处的单元刚度矩阵。这种改进的建模方法的第一步是基于两种模型的固有频率的相干性来确定单元刚度矩阵的修正系数,第二步是验证频率响应函数的相干性。本文还介绍了损伤单元刚度矩阵的算法和计算结果。还讨论了结构损伤位置和约束条件对小结构损伤修正系数的影响。

著录项

  • 作者

    Yan YJ; Yam LH; Cheng L; Yu L;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号