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基于导波监测的复合材料加筋结构冲击后剩余强度预测

Prediction of Residual Strength of Stiffened Composite Structure After Impact with Guided Waves-Based Monitoring

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【作者】 曾钰峻; 严刚; 芮鹏辉;

【Author】 ZENG Yujun;YAN Gang;RUI Penghui;State Key Laboratory of Mechanics and Control for Aerospace Structures, Nanjing University of Aeronautics & Astronautics;

【通讯作者】 严刚;

【机构】 南京航空航天大学航空航天结构力学及控制全国重点实验室;

【摘要】 对应用超声导波在线监测信息评估复合材料加筋结构冲击后剩余强度进行了研究。首先针对所监测的对象设计布置了压电传感网络并构建结构健康监测系统,通过局部信号差分系数计算出不同传感路径上的损伤指标,融合损伤概率成像方法识别损伤位置,测算形状因子以近似表征损伤尺寸。然后构建加筋结构有限元模型,由在线监测结果反馈损伤信息,采用软化夹杂法等效冲击损伤,依据复合材料损伤渐进失效分析理论,预测冲击后加筋结构的剩余极限强度。通过低速冲击、超声导波监测和压缩强度等一系列实验验证了所提出方法的有效性,为结构健康监测最高层次的应用提供基础。

【Abstract】 This paper investigates the prediction of residual strength of stiffened composite structure after impact with guided waves-based online monitoring information. Firstly, a piezoelectric sensor network is designed and implemented for the monitored structure, and a structural health monitoring system is established. Local signal difference coefficients are computed along different sensor paths to derive damage indicators, and a damage probability imaging method is employed to identify the location of damage, while the shape factor is estimated to approximate the size of the damage. Secondly, a finite element model is developed for the stiffened composite structure. Feedback from online monitoring results is used to model the damage, and softening inclusion methods are adopted to simulate the damage extent equivalently. By using the progressive failure analysis theory for composite, the residual ultimate strength of the stiffened composite structure after impact is predicted. The effectiveness of the proposed method is validated through a series tests of low-velocity impact, guided waves-based monitoring, and compressive strength, laying foundation for the highest level of application for structural health monitoring.

【基金】 国家自然科学基金(11602104);航空航天结构力学及控制全国重点实验室开放课题资助项目(MCMS-E-0423G02)
  • 【文献出处】 南京航空航天大学学报 ,Journal of Nanjing University of Aeronautics & Astronautics , 编辑部邮箱 ,2024年01期
  • 【分类号】V214.8
  • 【下载频次】36
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