Gong Guoliang, Lu Huaxiang, Chen Gang, Jin Min, Chen Xu
{"title":"基于快速ICA的正弦信号相位差测量方法","authors":"Gong Guoliang, Lu Huaxiang, Chen Gang, Jin Min, Chen Xu","doi":"10.1109/GCIS.2013.46","DOIUrl":null,"url":null,"abstract":"Noise is the key to cause phase measurement error of sine signals. Although there have been many attempts to suppress noise interference, high accuracy is still hard to meet in terrible noise environment. In order to improve reliability and accuracy of the measurement system, a robust method is proposed. In this paper, independent component analysis (ICA) is used to separate sine signal from noises. Firstly, an ICA model, which compensate the number of observed signals and its components is established. Then, the relationship of separation order of the independent components with measurement error is revealed, and a sorting algorithm based on priori knowledge is proposed to improve separation accuracy. Experimental results indicate the method is robust and accurate.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Phase Difference Measurement Method for Sine Signals Based on Fast ICA\",\"authors\":\"Gong Guoliang, Lu Huaxiang, Chen Gang, Jin Min, Chen Xu\",\"doi\":\"10.1109/GCIS.2013.46\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Noise is the key to cause phase measurement error of sine signals. Although there have been many attempts to suppress noise interference, high accuracy is still hard to meet in terrible noise environment. In order to improve reliability and accuracy of the measurement system, a robust method is proposed. In this paper, independent component analysis (ICA) is used to separate sine signal from noises. Firstly, an ICA model, which compensate the number of observed signals and its components is established. Then, the relationship of separation order of the independent components with measurement error is revealed, and a sorting algorithm based on priori knowledge is proposed to improve separation accuracy. Experimental results indicate the method is robust and accurate.\",\"PeriodicalId\":366262,\"journal\":{\"name\":\"2013 Fourth Global Congress on Intelligent Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth Global Congress on Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GCIS.2013.46\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth Global Congress on Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCIS.2013.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Phase Difference Measurement Method for Sine Signals Based on Fast ICA
Noise is the key to cause phase measurement error of sine signals. Although there have been many attempts to suppress noise interference, high accuracy is still hard to meet in terrible noise environment. In order to improve reliability and accuracy of the measurement system, a robust method is proposed. In this paper, independent component analysis (ICA) is used to separate sine signal from noises. Firstly, an ICA model, which compensate the number of observed signals and its components is established. Then, the relationship of separation order of the independent components with measurement error is revealed, and a sorting algorithm based on priori knowledge is proposed to improve separation accuracy. Experimental results indicate the method is robust and accurate.