基于数字图像相关的粘接界面内聚力模型参数反演识别

Inverse identification of cohesive model parameters using digital image correlation

胶接装配具有结构简单、质量小、尺寸小、工艺性好等优点,但脱胶破坏等界面失效形式的出现对胶接结构的使用提出了挑战。内聚力模型可以有效表征粘接界面的损伤失效过程,其参数的准确获取对粘接结构的可靠性分析和设计具有重要意义。文中提出了一种基于数字图像相关技术、有限元模拟计算和智能优化算法相结合的内聚力模型参数反演识别方法。首先,采用数字图像相关技术获取双悬臂梁试件在拉伸断裂过程中的粘接区域位移场;其次,基于双线性内聚力模型,建立双悬臂梁试件拉伸断裂的有限元模型,并仿真获得双悬臂梁试件粘接界面开裂过程的位移场信息;最后,采用人工鱼群优化算法迭代试算双线性内聚力模型参数,直至有限元仿真的位移场与数字图像相关技术获取的位移场之间的误差最小。

Adhesive assembly has the advantages of simple structure,lightweight,small size and good workmanship,but the emergence of interface failure forms,such as debonding damage,poses a challenge to the use of adhesive structures.The cohesive model can effectively characterize the damage failure process at the bonding interface,and the accurate acquisition of cohesive model parameters is of great significance for the reliable analysis and design of adhesive structures.An inverse identification method of cohesive model parameters based on the combination of digital image correlation technique,finite element simulation calculation,and intelligent optimization algorithm is proposed in this paper.Firstly,the digital image correlation technique is used to obtain the displacement field in the bonding area of the double cantilever beam specimen during the tensile fracture process;secondly,the corresponding finite element model is established,and the displacement fields are obtained by simulation;finally,the artificial fish swarm optimization algorithm is used to iteratively calculate the parameters of the cohesive model until the error between the measurement and the simulation is smallest.