复合材料在服役过程中易受到外部的低能量冲击, 造成不可见损伤, 为了监测复合材料健康状况, 将光纤布喇格光栅(FBG)传感网络粘贴布置于碳纤维复合材料表面, 采用基于反向传播（BP）神经网络系统的智能复合材料冲击定位识别技术, 获取FBG传感的时域信号响应值, 从而进行了复合材料冲击位置的预判。结果表明, BP神经网络算法具有非线性逼近能力强、容错率高和自适应能力强等优点, 可以实现复合材料层合板的参数化识别定位, 且预测结果与待测复合材料层合板总长度比值小于0.1。该FBG传感系统可为智能化复合材料冲击损伤自调整和自修复能力提供更准确的信息。

The composite material is susceptible to external low-energy impact which causes invisible damage during service. In order to achieve the purpose of monitoring the health of the composite material, the fiber Bragg grating (FBG) sensor network was pasted and arranged on the surface of the carbon fiber composite material. The intelligent composite material impact location recognition technology based on the back propagation (BP) neural network system was used to obtain the time-domain signal response value of the FBG sensor to predict the impact position of the composite material. The results show that the BP neural network algorithm has the advantages of strong nonlinear approximation ability, high fault tolerance and strong adaptive ability. It can realize the parameterized identification and positioning of composite laminates, and the ratio of the prediction results to the total length of the composite laminates to be tested less than 0.1. The FBG sensing system provides more accurate information for the self-adjustment and self-repair capabilities of intelligent composite materials.