Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (05): 53-58.doi: 10.13475/j.fzxb.20180503006

• Textile Engineering • Previous Articles     Next Articles

Structural damage identification of intelligent composite materials based on principal component analysis

WAN Li1(), GONG Liying2, JIA Minrui2   

  1. 1. Academic Affairs Office, Tianjin Medical University, Tianjin 300070, China
    2. Information Center, Tianjin Polytechnic University, Tianjin 300387, China
  • Received:2018-05-14 Revised:2019-02-12 Online:2019-05-15 Published:2019-05-21

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Abstract:

Aiming at the key problems in monitoring the structural state of three-dimensional braided composites, a method to build three-dimensional space-structured intelligent composite material was developed by embedding carbon nanotube yarns into the overall composites based on the three-dimensional six-directional braiding process. The damage index was adopte to realize the identification of the internal damage type of the intelligent composite specimen. For the internal damage of three-dimensional six-directional braided composite materials, four damage index performance characteristics were analyzed. Experiments show that combined damage index is better than the other three damage indexes and combined damage index can accurately identify the type of damage within the specimen. The three-dimensional braided composite material has small internal void damage and the combined damage index is less than 100. For internal crack damage of the composite specimen, combined damage index monitoring value is 300-500. When the combined damage index monitoring value is greater than 600, it can be judged that a large crack damage exists in the test specimens. Based on the damage index, the internal damage of the specimen can be calculated and the precision can reach 0.073 mm.

Key words: intelligent braided composite, three-dimensional six-directional braiding, principal component analysis, carbon nanotube yarn sensor, damage index

CLC Number: 

  • TS101.2

Fig.1

Schematic diagram of damage monitoring of 3-D braided composites specimen"

Fig.2

Schematic of three-dimensional braiding machine"

Fig.3

Schematic diagram of arrangement of carriers of three-dimensional six-directional braiding"

Fig.4

Three-dimensional six-directional composites preform embedded in carbon nanotube yarn"

Fig.5

Monitoring flowchart of internal damage for composite material based on PCA"

Tab.1

Parameters of 3-D braided composite materials"

编号 平均编织角/(°) 纤维体积含量/% 密度/(g·cm-3)
1# 30.4 57.1 1.55
2# 32.8 56.5 1.73
3# 29.5 52.1 1.64
4# 38.7 54.3 1.54

Fig.6

Test specimens"

Fig.7

T2 Damage index chart"

Fig.8

Q damage index chart"

Fig.9

Phi damage index chart"

Fig.10

I damage index chart"

[1] 刘振国, 亚纪轩, 林强, 等. 三维全五向编织复合材料细观结构实验分析[J]. 北京航空航天大学学报, 2016,42(6):211-216.
LIU Zhenguo, YA Jixuan, LIN Qiang, et al. Experimental analysis on micro-structure of three-dimensional full five-directional braided composites[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016,42(6):211-216.
[2] 张迪, 郑锡涛, 杨超. 三维编织复合材料损伤容限性能试验[J]. 复合材料学报, 2016,33(5):1048-1054.
ZHANG Di, ZHENG Xitao, YANG Chao. Damage tolerance property tests of 3D braided composites[J]. Acta Materiae Compositae Sinica, 2016,33(5):1048-1054.
[3] ZHANG Diantang, CHEN Li, SUN Ying. Meso-scale progressive damage of 3D five-directional braided composites under transverse compression[J]. Journal of Composite Materials, 2016,50(24):3345-3361.
[4] 朱虹. 天津工业大学助力“神舟十一”飞天[EB/OL]. , http://tj.people.com.cn/n2/2016/1018/c375366-29159662.html, 2016-10-18/2017-12-22.
ZHU Hong. ZHU Hong. Tianjin Polytechnic University helps ″Shenzhou Eleven″ flying[EB/OL]. http://tj.people.com.cn/n2/2016/1018/c375366-29159662.html, 2016-10-18/2017-12-22.
[5] 陈雪峰, 杨志勃, 田绍华, 等. 复合材料结构损伤识别与健康监测展望[J]. 振动、测试与诊断, 2018,38(1):1-10.
CHEN Xuefeng, YANG Zhibo, TIAN Shaohua, et al. A review of the damage detection and health monitoring for composite structures[J]. Journal of Vibration,Measurement & Diagnosis, 2018,38(1):1-10.
[6] 梁军, 杜善义, 韩杰才. 含夹杂和微裂纹复合材料的损伤演化和分析[J]. 固体力学学报, 1996,17(4):296-302.
LIANG Jun, DU Shanyi, HAN Jiecai. Damage evolution and analysis of composite materials with inclusions and microcracks[J]. Acta Mechanica Solida Sinica, 1996,17(4):296-302.
[7] BANAARA R P, CHAN T H T, THAMBIRATNAM D P. Structural damage detection method using frequency response functions[J]. Structural Health Monitoring, 2014,13(4):418-429.
[8] 黄红梅, 袁缜芳. 基于光纤Bragg光栅传感器的疲劳裂纹扩展的研究[J]. 光电子激光, 2009,20(4):447-450.
HUANG Hongmei, YUAN Shenfang. Research on the fatigue crack propagation using fiber Bragg grating sensors[J]. Journal of Optoelectronics Laser, 2009,20(4):447-450.
[9] 万振凯, 李嘉禄, 李怡. 光纤布拉格光栅在复合材料连续状态健康监测中的应用[J]. 纺织学报, 2011,32(8):57-61.
WAN Zhenkai, LI Jialu, LI Yi. Application of fiber Bragg grating to continuous monitoring health state of three dimensional braided composites[J]. Journal of Textile Research, 2011,32(8):57-61.
[10] 万莉, 郭建民, 马永军. 三维编织复合材料弯曲承载下嵌入碳纳米线的特性分析[J]. 纺织学报, 2016,37(1):57-63.
WAN Li, GUO Jianmin, MA Yongjun. Bending load characteristic of carbon nano wires embedded into three-dimensional braided composite[J]. Journal of Textile Research, 2016,37(1):57-63.
[11] 万振凯, 贡丽英, 万莉. 基于损伤指数的三维编织复合材料结构损伤评估[J]. 纺织学报, 2017,38(5):69-74.
WAN Zhenkai, GONG Liying, WAN Li. Structural damage evaluation of three dimensional braided composite based on damage index[J]. Journal of Textile Research, 2017,38(5):69-74.
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