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

doi:10.13475/j.fzxb.20210101907

纺织学报 ›› 2021, Vol. 42 ›› Issue (09): 76-82.doi: 10.13475/j.fzxb.20210101907

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

万振凯¹(), 贾敏瑞², 包玮琛²

1.天津工业大学工程教学中心, 天津 300387
2.天津工业大学纺织科学与工程学院, 天津 300387

收稿日期:2021-01-11 修回日期:2021-03-17 出版日期:2021-09-15 发布日期:2021-09-27
作者简介:万振凯(1964—),男,教授,博士。主要研究方向为三维编织复合材料检测方法。E-mail: wanzhenkai@tiangong.edu.cn。

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

WAN Zhenkai¹(), JIA Minrui², BAO Weichen²

1. Engineering Teaching Center, Tiangong University, Tianjin 300387, China
2. School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China

Received:2021-01-11 Revised:2021-03-17 Published:2021-09-15 Online:2021-09-27

摘要/Abstract

摘要：

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。

关键词: 碳纳米管纱线, 非支配邻域免疫算法, 传感器优化配置, 损伤定位源, 三维编织复合材料

Abstract:

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.

Key words: carbon nanotube yarn, nondominated neighborhood imnaune algorithm, optimal allocation of sensors, damage location source, 3-D braided composite

中图分类号:

TS101.2

万振凯, 贾敏瑞, 包玮琛. 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[J]. 纺织学报, 2021, 42(09): 76-82.

WAN Zhenkai, JIA Minrui, BAO Weichen. Optimal configuration of embedded position and number of carbon nanotube yarns in 3-D braided composites[J]. Journal of Textile Research, 2021, 42(09): 76-82.

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试件尺寸	传感网络总覆盖率/%	轴向传感器数量	纬向传感器数量	轴向传感器位置	纬向传感器位置
6 cm×1 cm	69.5	2	4	{1,7}	{1,5,8,11}
6 cm×1 cm	62.9	2	5	{1,7}	{1,3,7,10,12}
6 cm×1 cm	70.1	3	4	{1,4,7}	{1,3,7,10,12}
6 cm×2 cm	77.8	4	4	{2,8,14,19}	{1,5,8,11}
6 cm×2 cm	79.5	5	4	{1,5,10,15,19}	{1,5,8,11}
8 cm×1 cm	74.6	2	6	{1,7}	{1,4,7,10,13,16}
8 cm×1 cm	70.4	2	5	{1,7}	{1,5,8,13,16}
8 cm×1 cm	71.2	3	5	{1,4,7}	{1,5,8,13,16}
10 cm×10 cm	90.4	20	7	{1,3,5,7,9,11,13,15,17,19}	{1,4,7,10,13,16,19}
20 cm×20 cm	91.8	40	13	{1,6,11,16,21,26,31,36,41,46, 51,56,61,66,71,76,81,86,91,96, 100,105,110,115,120,125,130, 135,140,145,150,155,160,165, 170,175,180,185,190,195,200}	{1,4,7,11,14,17,21, 24,27,31,34,37,40}

损伤编号	损伤计算坐标	损伤实际坐标	坐标最大偏差/mm
A	(-3.0,2.4)	(-2.3,2.5)	0.5
B	(-2.3,18.4)	(-2.1,18.2)	0.08
C	(-3.2,1.5)	(-3.4,1.1)	0.2
D	(-4.6,13.1)	(-4.9,12.8)	0.58
E	(-2.6,-3.8)	(-2.5,-3.5)	0.1
F	(-4.1,-7.8)	(-4.3,-7.5)	0.13

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

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

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