基于光纤Bragg光栅和支持向量机的冲击损伤识别研究

Identification of impact damage based on FBG and SVM technology

针对常用无损检测的局限性,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。

Aiming at the limitation of common non-destructive technology,an active real-time monitoring system based on fiber Bragg grating sensors was set up here-in.Support vector machine(SVM)was used to detect the impact damage for carbon fiber composite laminated plates,and compare the identified results with those using the traditional BP neural network.The study results showed 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 level of impact damage effectively.