光时域反射计
特征提取
时域
模式识别(心理学)
计算机科学
人工智能
特征向量
特征(语言学)
信号(编程语言)
频域
灵敏度(控制系统)
噪音(视频)
特征选择
工程类
计算机视觉
电子工程
光纤传感器
光纤
电信
渐变折射率纤维
程序设计语言
语言学
哲学
图像(数学)
作者
Qian Sun,Hao Feng,Yan Xueying,Zhoumo Zeng
出处
期刊:Sensors
[MDPI AG]
日期:2015-06-29
卷期号:15 (7): 15179-15197
被引量:120
摘要
This paper proposes a novel feature extraction method for intrusion event recognition within a phase-sensitive optical time-domain reflectometer (Φ-OTDR) sensing system. Feature extraction of time domain signals in these systems is time-consuming and may lead to inaccuracies due to noise disturbances. The recognition accuracy and speed of current systems cannot meet the requirements of Φ-OTDR online vibration monitoring systems. In the method proposed in this paper, the time-space domain signal is used for feature extraction instead of the time domain signal. Feature vectors are obtained from morphologic features of time-space domain signals. A scatter matrix is calculated for the feature selection. Experiments show that the feature extraction method proposed in this paper can greatly improve recognition accuracies, with a lower computation time than traditional methods, i.e., a recognition accuracy of 97.8% can be achieved with a recognition time of below 1 s, making it is very suitable for Φ-OTDR system online vibration monitoring.
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