摘要
相位敏感光时域反射计(Φ-OTDR)已广泛应用在防入侵检测、建筑结构的裂缝健康检测和管道检测,但其准确性和抗噪性能还需要提高。提出了一种基于Φ-OTDR的智能识别系统,该系统采用神经网络算法进行智能识别,并对振动强度进行识别概率化处理。实验结果表明:提出的系统能够准确识别并定位入侵行为,定位精度达到5 m以内。
The phase-sensitive optical time domain reflectometer(Φ-OTDR)has been widely used in anti-intrusion,crack health detection of building structure and pipeline detection,but the accuracy and anti-noise still need to be improved.In this paper,theΦ-OTDR intelligent recognition system is proposed.Through intelligent identification by neural network algorithm and the vibration intensity is identification with probability processing.The experimental results show that the proposed system can accurately identify and locate the intrusion behavior,and the positioning accuracy is within 5 m.
作者
唐超
林靖凯
欧阳竑
王侠
李沼云
TANG Chao;LIN Jingkai;OU Yanghong;WANG Xia;LI Zhaoyun(The 34th Research Institute of CETC,Guilin Guangxi 541004,China;National University of Defense Technology,PLA,Changsha 410073,China)
出处
《光通信技术》
2022年第3期8-12,共5页
Optical Communication Technology
基金
广西科技重大专项(AA19254015)资助。
关键词
相位敏感光时域反射计
入侵检测
特征提取
phase-sensitive optical time domain reflectometer
intrusion detection
feature extraction
