针对常用无损检测的局限性，本文基于光纤Bragg光栅传感器搭建了冲击损伤实时主动监测系统，结合支持向量机算法对碳纤维飞行器壁板进行了冲击损伤位置及程度的识别研究，并与传统的BP神经网络识别结果进行了对比。结果表明：支持向量机算法具有较好的函数回归能力，且该系统能实时有效地从冲击前后的信号中识别出冲击损伤的位置及程度，对冲击损伤识别具有较高的精度。

Aim at the limitation of common non-destructive technology, an active real-time monitoring system based on the fiber Bragg grating sensors is set up in this paper. Support Vector Machine (SVM) is applied to detect the impact damage for the carbon fiber composite laminated plates, and compared with the traditional BP neural network. The results show that SVM possesses the better ability of regression and higher accuracy than the traditional BP neural network. Furthermore, the monitoring system can identify the locations and degrees of impact damage real-time effectively.