S. Artemova, A. I. Ladynin, Tri Vu Chien, M. M. Kamenskaia, Tatiana A. Ryabchik
{"title":"膏体材料快速评估方法","authors":"S. Artemova, A. I. Ladynin, Tri Vu Chien, M. M. Kamenskaia, Tatiana A. Ryabchik","doi":"10.1109/ElConRus51938.2021.9396353","DOIUrl":null,"url":null,"abstract":"During drying process control according to the manufactured products and productivity quality loss minimization criteria, an important task is rapid pasty materials moisture assessment. Due to a control object features number, the drying process, or the control process itself, the known measuring devices cannot be used to achieve the criteria formulated above. Therefore, a method is proposed for the paste material moisture rapid assessment during its drying. The method features neural networks, built on pasty materials drying process most influent parameters’ significant sample basis. The article provides the described method usage example implementing device. The developed method makes it possible to evaluate pasty material moisture during its drying in real-time with a relative error less than 2%, which makes rapid control action synthesis possible, aimed to minimize the desired criteria.","PeriodicalId":447345,"journal":{"name":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pasty Materials Prompt Assessment Method\",\"authors\":\"S. Artemova, A. I. Ladynin, Tri Vu Chien, M. M. Kamenskaia, Tatiana A. Ryabchik\",\"doi\":\"10.1109/ElConRus51938.2021.9396353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"During drying process control according to the manufactured products and productivity quality loss minimization criteria, an important task is rapid pasty materials moisture assessment. Due to a control object features number, the drying process, or the control process itself, the known measuring devices cannot be used to achieve the criteria formulated above. Therefore, a method is proposed for the paste material moisture rapid assessment during its drying. The method features neural networks, built on pasty materials drying process most influent parameters’ significant sample basis. The article provides the described method usage example implementing device. The developed method makes it possible to evaluate pasty material moisture during its drying in real-time with a relative error less than 2%, which makes rapid control action synthesis possible, aimed to minimize the desired criteria.\",\"PeriodicalId\":447345,\"journal\":{\"name\":\"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ElConRus51938.2021.9396353\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ElConRus51938.2021.9396353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
During drying process control according to the manufactured products and productivity quality loss minimization criteria, an important task is rapid pasty materials moisture assessment. Due to a control object features number, the drying process, or the control process itself, the known measuring devices cannot be used to achieve the criteria formulated above. Therefore, a method is proposed for the paste material moisture rapid assessment during its drying. The method features neural networks, built on pasty materials drying process most influent parameters’ significant sample basis. The article provides the described method usage example implementing device. The developed method makes it possible to evaluate pasty material moisture during its drying in real-time with a relative error less than 2%, which makes rapid control action synthesis possible, aimed to minimize the desired criteria.