考虑螺栓球节点半刚性的网格结构有限元模型修正研究

为获取用于螺栓球节点网格结构健康监测准确有限元模型，用具有刚度可调节点单元描述节点半刚性；采用神经网络技术，利用有限测点模态信息构造网络输入参数CPFM，提出对螺栓球节点单元刚度折减系数进行分步修正新方法。以单层柱面网壳振动台试验模型为例，在螺栓球节点精细化模型基础上，基于实测模态数据对其进行有限元模型修正。结果表明，修正后有限元模型能较好反映该网壳结构的真实动力特性，采用分步修正算法能精简神经网络结构，可有效用于螺栓球节点网格结构有限元模型修正，具有一定实用价值。

Study on finite element model updating of single-layer latticed cylindrical shell in consideration of semi-rigid characters of the bolt-ball joint

In order to get a more accurate finite element analysis model of the bolt-ball shell for health monitoring, the element in adjustable stiffness model is used to reveal the semi-rigid characters of the node. Then, the neural network technology is introduced, by forming network input parameter CPFM with limited measuring point information. A new method of the recognition of the rigid factor, in consideration of the semi-rigid character of the joint reasonably, is put forward by the combination of the elements. A single-layer latticed cylindrical shell with 157 nodes and 414 elements experiment model was used for shaking table test. Based on the basic model and measured modal data, a finite element model updating is done. The result shows that the true dynamic characters of the shell structure can be reflected better, at the same time the neural network can be simplified by applying step-by-step correction algorithm. The result shows that the method can be used for model updating of the bolt-ball shell and certain value in engineering practice.