一种用于光纤链路振动信号模式识别的规整化复合特征提取方法

相位光时域反射链路监测系统是一种利用光纤作为传感介质的传感系统, 能够监测、定位、识别入侵信号.模式识别模块是其重要组成部分, 实时智能区分安全扰动和危险入侵.本文提出一种用于光纤链路振动信号模式识别的复合特征提取方法.利用改进的双门限方法确定有效信号段的起止位置, 结合最大能量与最高信噪比挑选出采样周期内主要入侵扰动的特征段.综合利用特征段时域持续时间和小波包能量谱提取复合特征向量, 使用支持向量机进行模式识别.实验表明, 基于本文提出的规整化特征提取方法的模式识别准确率有了显著提高.

A regular composite feature extraction method for vibration signal pattern recognition in optical fiber link system

Phase optical time-domain reflectometer link monitoring system is a kind of sensor system which uses optical fiber as sensing medium. It can detect, recognize and locate invasive signals. The module of pattern recognition, which is one of the important parts of the system, can intelligently and instantly distinguish dangerous intrusions from safe disturbances. This paper proposes a regular composite feature extraction method which can be used for vibrational signal pattern recognition in an optical fiber monitoring system. This method applies an improved double-threshold method to detect the start-stop positions of the valid signal segments, and then combines the maximum energy and maximum signal noise ratio to select the main invasion feature segment within a sampling period. The composite eigenvectors, which are extracted by using the last time of the feature segment and wavelet packet energy spectrum, can be used by the support vector machine to recognize the signal patterns. Experiment results show that the accuracy rate of the pattern recognition has been improved significantly based on the proposed method in this paper.