基于时频特征的光纤周界振动信号识别

The Vibration Signal Recognition of Optical Fiber Perimeter Based on Time-frequency Features

在光纤周界安防系统中,蓄意入侵和环境噪声均能引起光纤传感器振动,在保证系统高灵敏度的前提下区分入侵和非入侵事件极为重要。为了有效识别各种光纤振动信号,本文依据入侵和环境噪声引起的光纤振动信号在时域上的短时特性以及复小波域各尺度上能量分布特征,提出了两级判别法识别光纤信号。第一级用时域特征,短时能量和短时平均过零率判断是否有振动发生;第二级用复小波提取光纤信号的能量分布特征,联合时域特征形成特征矢量,支持向量机(SVM)作为分类器识别是否为入侵信号及入侵类型。实验结果表明,此方法可以有效识别入侵信号和环境噪声引起的非入侵事件,提高了系统报警率,降低了误报率。

In the optical fiber perimeter security system, both deliberate invasion and environmental noise can cause optical fiber sensor vibration. It is very important to distinguish the invasion and no invasion events under ensuring the high sensitivity of system. In order to identify the various fiber optic vibration signals effectively, we propose two-stage discriminative method based on the invasion and environmental noise vibration signals short features on time-domain as well as scale energy distribution on complex wavelet domain to recognize the fiber optic signal. The first level use the time-domain characteristics of short-time energy and short-time zero crossing rate to judge whether there is a vibration happening. The second level use complex wavelet extraction the energy distribution features, combining with the time domain characteristics form the characteristic vector, Support Vector Machine （SVM） as the classifier to identify whether it is a intrusion signal and intrusion type. The experiment results show that this method can identify the intrusion signals and environment noise signals effectively, improve the system alarm rate and reduce the nuisance alarm rate.