{"title":"Temperature Calculation of Pellet Rotary Kiln Based on Texture","authors":"Chunli Lin, Yufan Wu","doi":"10.4236/ICA.2017.82005","DOIUrl":null,"url":null,"abstract":"In order to improve the quality of clinker produced by pellet rotary kiln, flame temperature that it is a very important factor of affecting on the quality of clinker is studied. The flame images collected from pellet rotary kiln are decomposed into three gray images by the method of RGB, so we can get more information of flame. Taking advantage of gray level co-occurrence matrix, the monitoring model for flame temperature based on image texture is established with RGB channels. In order to test the universality of the algorithm, candle flame temperature is detected by this method. The maximum error of the model is less than 3%.","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"08 1","pages":"67-74"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"智能控制与自动化(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.4236/ICA.2017.82005","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
In order to improve the quality of clinker produced by pellet rotary kiln, flame temperature that it is a very important factor of affecting on the quality of clinker is studied. The flame images collected from pellet rotary kiln are decomposed into three gray images by the method of RGB, so we can get more information of flame. Taking advantage of gray level co-occurrence matrix, the monitoring model for flame temperature based on image texture is established with RGB channels. In order to test the universality of the algorithm, candle flame temperature is detected by this method. The maximum error of the model is less than 3%.