多源信息融合的光纤传感网络异常行为检测研究

Research on abnormal behavior detection of optical fiber sensor network based on multi-source information fusion

为降低光纤传感网络异常行为检测偏差,提出了基于多源信息融合的光纤传感网络异常行为检测方法。首先分析光纤传感网络异常行为检测原理,并采集光纤传感网络异常行为的多源信息,然后采用神经网络对光纤传感网络异常行为的多源信息进行学习,拟合光纤传感网络异常行为变化特点,设计光纤传感网络异常行为检测的分类器,最后采用VC++编程实现光纤传感网络异常行为检测实验,多源信息融合的光纤传感网络异常行为检测正确率超过90%,光纤传感网络异常行为误检、漏检均低于10%,可以满足光纤传感网络安全,检测结果要优于其它方法,验证了本文光纤传感网络异常行为检测方法的优势。

in order to reduce the detection error of abnormal behavior in optical fiber sensor network,a method of abnormal behavior detection based on multi-source information fusion is proposed.Firstly,the principle of abnormal behavior detection of optical fiber sensor network is analyzed,and the multi-source information of abnormal behavior of optical fiber sensor network is collected.Then,neural network is used to learn the multi-source information of abnormal behavior of optical fiber sensor network,and the characteristics of abnormal behavior change of optical fiber sensor network are fitted.Finally,the abnormal behavior detection classifier of optical fiber sensor network is designed.Finally,optical fiber sensing is realized by VC++programming Network abnormal behavior detection experiment,multisource information fusion of optical fiber sensor network abnormal behavior detection accuracy is more than 90%,optical fiber sensor network abnormal behavior false detection,missed detection are less than 10%,can meet the optical fiber sensor network security,detection results are better than other methods,verify the advantages of the optical fiber sensor network abnormal behavior detection method.