基于立体式光纤传感网络的大尺寸复合材料夹芯板健康监测

Health monitoring of large-sized composite sandwich panels based on three-dimensional optical fiber sensing network

  • 摘要: 碳纤维增强树脂基复合材料由于其轻质高强的优异性能得到普遍关注,其中的夹芯结构由于功能性多样化且可设计性强而受到越来越广泛的应用,然而芯材和面板界面服役过程容易出现内部损伤,降低结构承载能力。本文结合内埋式光栅阵列光纤在大尺寸复合材料夹芯板内部构成立体式光纤传感网络,进行冲击前四点弯曲、低速冲击和冲击后四点弯曲等试验,实现动静态载荷作用下不同厚度不同部位应变的原位监测。提取冲击应变峰值结合基于粒子群优化算法的高斯回归算法对冲击能量进行预测,预测结果与实际结果吻合良好。同时冲击损伤出现后界面处局部刚度出现显著下降,夹芯板结构承载能力下降,弥补宏观载荷-位移曲线无法提供局部损伤信息的不足。立体式光纤传感网络可以有效实现对复合材料夹芯结构服役期间的冲击过程感知和芯材和面板界面处冲击损伤的实时健康监测,为保障复合材料夹芯结构的服役安全性提供有效信息。

     

    Abstract: The Carbon fiber reinforced plastics (CFRPs) have gained wide attention due to their excellent properties including light weight and high-strength. Among them, the sandwich structure, due to its diverse functions and strong designability, has been increasingly widely applied. However, the internal damage is prone to occur at the interface between the core material and panel during the service stage, reducing the structural loading capacity. The Fiber Bragg Grating (FBG) arrays embedded inside the large-sized composite sandwich plates form a three-dimensional fiber sensing network. The tests including the pre-impact four-point bending, low-velocity impact, and post-impact four-point bending were carried to achieve the in-situ monitoring of strains at different thicknesses under dynamic and static loads. The peak strains during the impact test were extracted and the impact energies were predicted using the Gaussian process regression based on the particle swarm optimization algorithm. The prediction results were in good agreement with the actual impact energies. After the inside damage occurs, the local stiffness at the interface decreased significantly, and the loading capacity of the sandwich plate decreased. The FBG arrays provide local damage information and compensate the deficiency of the macroscopic load-displacement curve. The three-dimensional fiber sensing network can effectively realize the sensing of the impact process of the composite sandwich structure and the real-time health monitoring of impact damage at the interface between the core material and panel, which provides effective information for ensuring the service safety of the composite sandwich structure.

     

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