K. Masalimov, S. I. Fecak, R. Munasypov, Yu. V. Idrisova
{"title":"金属切割机模块的运行诊断方法","authors":"K. Masalimov, S. I. Fecak, R. Munasypov, Yu. V. Idrisova","doi":"10.1109/SUMMA48161.2019.8947581","DOIUrl":null,"url":null,"abstract":"The work is devoted to solving the problem online diagnostics of machine tools modules using data-based models. The authors propose a diagnostic method that includes models based on long short-term neural memory networks as a repository of frequency reference values. An experimental result of the application is given.","PeriodicalId":163496,"journal":{"name":"2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Method of Operational Diagnostics of Metal Cutting Machine Modules\",\"authors\":\"K. Masalimov, S. I. Fecak, R. Munasypov, Yu. V. Idrisova\",\"doi\":\"10.1109/SUMMA48161.2019.8947581\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The work is devoted to solving the problem online diagnostics of machine tools modules using data-based models. The authors propose a diagnostic method that includes models based on long short-term neural memory networks as a repository of frequency reference values. An experimental result of the application is given.\",\"PeriodicalId\":163496,\"journal\":{\"name\":\"2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SUMMA48161.2019.8947581\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SUMMA48161.2019.8947581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Method of Operational Diagnostics of Metal Cutting Machine Modules
The work is devoted to solving the problem online diagnostics of machine tools modules using data-based models. The authors propose a diagnostic method that includes models based on long short-term neural memory networks as a repository of frequency reference values. An experimental result of the application is given.