三维编织复合材料中碳纳米管纱线嵌入位置和数量的优化配置

为解决三维编织复合材料嵌入碳纳米管(CNT)纱线传感器优化配置目标多、目标函数不连续问题,实现航天结构制件内部损伤的全面监测,采用非支配邻域免疫算法对多目标优化问题进行了研究。以四步法三维六向编织工艺为依据,分析了CNT纱线传感器的最佳嵌入位置和数量;通过非支配邻近免疫算法实现了CNT纱线传感器优化配置问题的求解,推导出不同尺寸的三维编织复合材料制件嵌入传感器的最优数量和位置。对损伤制件的应力实验及数据分析证明,CNT纱线传感器优化配置结果适用于三维编织复合材料的损伤监测,损伤定位误差小于0.6 mm。该研究为复合材料损伤源定位模型的建立提供参考。

Optimal configuration of embedded position and number of carbon nanotube yarns in 3-D braided composites

In order to facilitate comprehensive monitoring of the internal damage of aerospace structures, the optimal configuration of 3-D intelligent braided composites embedded with carbon nanotube(CNT)yarns as sensors with multiple targets and discontinuous objective function was studied by using the non-dominant neighborhood immune multi-target optimization algorithm. In this paper, the optimal insertion location and quantity of CNT yarn sensors were analyzed based on the three-dimension-four-step-six-direction braiding process. The optimal allocation problem of CNT yarn sensor was solved by using the non-dominant neighborhood immune multi-objective optimization algorithm, and the optimal number and location of different specimen embedded sensors in the 3-D intelligent braided composite were derived. The stress experiment and data analysis on the damaged specimens prove that the principle of optimal configuration of CNT yarn sensor can be applied for damage monitoring of 3-D braided composite materials with the positioning error less than 0.6 mm. This study lays a foundation for the establishment of intelligent composite damage source identification model.