{"title":"基于Hilbert变换的土壤振动信号提取","authors":"Shangqing Hao, Guangshun Shi, Kai Wang, H. Yan","doi":"10.1109/ICSESS.2010.5552374","DOIUrl":null,"url":null,"abstract":"This paper researches on real-time noise reduction and segmentation method of soil vibration signals collected by the fiber optic laid in the vicinity of oil pipeline. First, we extract valid fragments of signals using the self-correlation coefficient. Then Hilbert transform is performed to reduce noise and enhance on those extracted fragments. Finally, we collect vibration signals caused by destructive events with dual-threshold method. Real application showed that the method proposed in this paper is robust and accurate enough to extract all the signals of our interest, making a great contribution to improving the performance in the following classification stage.","PeriodicalId":264630,"journal":{"name":"2010 IEEE International Conference on Software Engineering and Service Sciences","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extraction of the soil vibration signal based on Hilbert transform\",\"authors\":\"Shangqing Hao, Guangshun Shi, Kai Wang, H. Yan\",\"doi\":\"10.1109/ICSESS.2010.5552374\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper researches on real-time noise reduction and segmentation method of soil vibration signals collected by the fiber optic laid in the vicinity of oil pipeline. First, we extract valid fragments of signals using the self-correlation coefficient. Then Hilbert transform is performed to reduce noise and enhance on those extracted fragments. Finally, we collect vibration signals caused by destructive events with dual-threshold method. Real application showed that the method proposed in this paper is robust and accurate enough to extract all the signals of our interest, making a great contribution to improving the performance in the following classification stage.\",\"PeriodicalId\":264630,\"journal\":{\"name\":\"2010 IEEE International Conference on Software Engineering and Service Sciences\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Software Engineering and Service Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSESS.2010.5552374\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Software Engineering and Service Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2010.5552374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extraction of the soil vibration signal based on Hilbert transform
This paper researches on real-time noise reduction and segmentation method of soil vibration signals collected by the fiber optic laid in the vicinity of oil pipeline. First, we extract valid fragments of signals using the self-correlation coefficient. Then Hilbert transform is performed to reduce noise and enhance on those extracted fragments. Finally, we collect vibration signals caused by destructive events with dual-threshold method. Real application showed that the method proposed in this paper is robust and accurate enough to extract all the signals of our interest, making a great contribution to improving the performance in the following classification stage.