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.