Wang Baozhu , Li Wenjuan , Peng Kai , Wang Qiang , Li Meili
{"title":"基于时间序列分析的光栅信号时域细分方法","authors":"Wang Baozhu , Li Wenjuan , Peng Kai , Wang Qiang , Li Meili","doi":"10.13494/j.npe.20170041","DOIUrl":null,"url":null,"abstract":"<div><p>Aiming at the restriction of the Moire signal quality on the subdivision multiple and accuracy, a time domain subdivision method for optical grating signals based on time series analysis is proposed. The relationship between the grating pitch and the sampling period is utilized to transform the equal space intervals into time series. A time domain prediction model is established based on the autoregressive model of time series analysis to predict the sampling time, and the parameters of the model are calculated using the maximum likelihood estimate method. Experimental results indicate that the subdivision errors both achieve ± 2.4\" when the subdivision multiples are 400 and 800, respectively. This subdivision method reduces the reliance on grating signal quality, proving certain application value.</p></div>","PeriodicalId":87330,"journal":{"name":"Nanotechnology and Precision Engineering","volume":"1 1","pages":"Pages 48-53"},"PeriodicalIF":2.7000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.13494/j.npe.20170041","citationCount":"2","resultStr":"{\"title\":\"Time Domain Subdivision Method for Optical Grating Signal Based on Time Series Analysis\",\"authors\":\"Wang Baozhu , Li Wenjuan , Peng Kai , Wang Qiang , Li Meili\",\"doi\":\"10.13494/j.npe.20170041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Aiming at the restriction of the Moire signal quality on the subdivision multiple and accuracy, a time domain subdivision method for optical grating signals based on time series analysis is proposed. The relationship between the grating pitch and the sampling period is utilized to transform the equal space intervals into time series. A time domain prediction model is established based on the autoregressive model of time series analysis to predict the sampling time, and the parameters of the model are calculated using the maximum likelihood estimate method. Experimental results indicate that the subdivision errors both achieve ± 2.4\\\" when the subdivision multiples are 400 and 800, respectively. This subdivision method reduces the reliance on grating signal quality, proving certain application value.</p></div>\",\"PeriodicalId\":87330,\"journal\":{\"name\":\"Nanotechnology and Precision Engineering\",\"volume\":\"1 1\",\"pages\":\"Pages 48-53\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.13494/j.npe.20170041\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nanotechnology and Precision Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589554018300370\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nanotechnology and Precision Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589554018300370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time Domain Subdivision Method for Optical Grating Signal Based on Time Series Analysis
Aiming at the restriction of the Moire signal quality on the subdivision multiple and accuracy, a time domain subdivision method for optical grating signals based on time series analysis is proposed. The relationship between the grating pitch and the sampling period is utilized to transform the equal space intervals into time series. A time domain prediction model is established based on the autoregressive model of time series analysis to predict the sampling time, and the parameters of the model are calculated using the maximum likelihood estimate method. Experimental results indicate that the subdivision errors both achieve ± 2.4" when the subdivision multiples are 400 and 800, respectively. This subdivision method reduces the reliance on grating signal quality, proving certain application value.