LU Na, AN Bo-wen, LI Yu-lian, et al. Signal recognition algorithm of fiber-optic security system based on time-domain features[J]. 2017, 36(4): 150-152.
LU Na, AN Bo-wen, LI Yu-lian, et al. Signal recognition algorithm of fiber-optic security system based on time-domain features[J]. 2017, 36(4): 150-152. DOI: 10.13873/J.1000-9787(2017)04-0150-03.
基于时域特征的光纤安防系统信号识别算法
摘要
在分布式光纤周界安防系统中
为实时有效分辨出系统所受的入侵事件和干扰事件
提出了一种基于时域特征的振动信号模式识别算法。对原始振动信号进行降噪处理
然后提取降噪后信号的短时能量和短时过阈值率两类特征值
将提取的特征值作为特征向量输入到支持向量机(SVM)中进行训练和测试
建立分类模型
将分类模型应用于安防系统
实时识别出入侵和干扰事件。实验结果可知:模式识别算法的分类效率高
误差小
具有有效性和可行性。
Abstract
In distributed optical fiber perimeter security system
in order to recognize intrusion and interference events effectively in realtime
a vibration signal pattern recognition algorithm based on time-domain features in actual optical fiber perimeter security system is proposed. Original vibration signal is processed to reduce the noise
short-term energy and short-term threshold rate are extracted and formed feature vector. Next
the feature vector is input into support vector machine( SVM) for training and test and establish classification model
which is used to security system and recognize intrusion and interference event. Experimental results show that the pattern recognition algorithm classification is high-efficiency