%0 Journal Article
%T 考虑耦合特性的多螺栓连接结合部等效建模
Equivalent Modeling of Multi-Bolt Joint Union Considering Coupling Characteristics
%A 陈学敏
%A 许龙
%A 夏俊杰
%J Modeling and Simulation
%P 315-323
%@ 2324-870X
%D 2025
%I Hans Publishing
%R 10.12677/mos.2025.141030
%X 为提高多螺栓连接结合部的仿真精度，本文基于虚拟材料提出了一种综合考虑结合部接触压力分布不均匀性和相邻螺栓间耦合特性的等效建模方法。以多螺栓连接板结构为例，根据结合部实际接触压力分布情况对虚拟材料层进行分区域处理，各区域虚拟材料层材料参数由该区域的接触特性决定，从而建立结合部的等效模型。通过深度神经网络模型替代复杂的有限元数值计算模型，并使用粒子群优化算法辨识各虚拟材料层材料参数。仿真结果表明：该模型的模态频率偏差均小于1.9%，且模态振型与实验结果一致，验证了所提方法的有效性。
In order to improve the simulation accuracy of multi-bolt connection bond, this paper proposes an equivalent modeling method based on the virtual material, which integrally considers the contact pressure distribution inhomogeneity of the bond and the coupling characteristics between adjacent bolts. Taking the multi-bolt connection plate structure as an example, the virtual material layer is processed in a subregion according to the actual contact pressure distribution in the bond, and the material parameters of the virtual material layer in each region are determined by the contact characteristics of the region, so as to establish the equivalent model of the bond. A deep neural network model is used to replace the complex finite element numerical calculation model, and a particle swarm optimization algorithm is used to identify the material parameters of each virtual material layer. The simulation results show that the modal frequency deviations of the model are all less than 1.9%, and the modal vibration shapes are consistent with the experimental results, which verifies the effectiveness of the proposed method.
%K 多螺栓连接结合部，
%K 虚拟材料，
%K 深度神经网络，
%K 模态试验，
%K 粒子群优化算法
Multi-Bolt Joint
%K Virtual Material
%K Deep Neural Network
%K Modal Test
%K Particle Swarm Optimization Algorithm
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=104965