Zhiyong Sheng, Tingliang Feng, Yanping Wang, Jun Fan
{"title":"The Characteristic Extraction Method of Fiber Intrusion Signals Based on Band Cutting and Imaging","authors":"Zhiyong Sheng, Tingliang Feng, Yanping Wang, Jun Fan","doi":"10.1109/CISP-BMEI.2018.8633165","DOIUrl":null,"url":null,"abstract":"This thesis put forward a band cutting and imaging to extract characteristic for optical fiber intrusion signals. Firstly, frequency-time distribution of every dimensional intrusion location is obtained by the frequency-time analysis technique of original collected signals. Then, energy band integral goes along the frequency direction. The 2-D images are further stacked to form layers, leading to 3-D space-time-frequency cubic data. Lastly, the corresponding time and space feature spectrum based on the 3-D cube data is as the feature of the intrusion signals. The actual data experiments show that multi-band cutting and imaging is a very effective method for feature extraction and type identification of fiber-optic intrusion signals.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2018.8633165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This thesis put forward a band cutting and imaging to extract characteristic for optical fiber intrusion signals. Firstly, frequency-time distribution of every dimensional intrusion location is obtained by the frequency-time analysis technique of original collected signals. Then, energy band integral goes along the frequency direction. The 2-D images are further stacked to form layers, leading to 3-D space-time-frequency cubic data. Lastly, the corresponding time and space feature spectrum based on the 3-D cube data is as the feature of the intrusion signals. The actual data experiments show that multi-band cutting and imaging is a very effective method for feature extraction and type identification of fiber-optic intrusion signals.