{"title":"基于AI的智能EOCR电机系统状态鉴别器","authors":"Kyung-Min Lee, Chul-Won Park","doi":"10.5207/jieie.2023.37.5.070","DOIUrl":null,"url":null,"abstract":"Recently, there has been growing interest in applying AI (artificial intelligence) technology to predict electric motor defect, perform prevention and maintenance, and reduce recovery costs and losses. This paper proposes an AI-based state discriminator for the electric motor system to improve the existing EOCR into a smart EOCR by adding the predictive maintenance function of the CLOUD environment. Firstly, the smart EOCR based motor system is introduced. Next, five state learning data sets collected from the motor system are constructed. After designing a state discriminator with DNN (Deep Neural Network), a widely used AI technique, and implementing it using the Python language. We prove the effectiveness of the state discriminator.","PeriodicalId":488820,"journal":{"name":"Journal of The Korean Institute of Illuminating and Electrical Installation Engineers","volume":"204 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI Based State Discriminator of Motor System for Smart EOCR\",\"authors\":\"Kyung-Min Lee, Chul-Won Park\",\"doi\":\"10.5207/jieie.2023.37.5.070\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, there has been growing interest in applying AI (artificial intelligence) technology to predict electric motor defect, perform prevention and maintenance, and reduce recovery costs and losses. This paper proposes an AI-based state discriminator for the electric motor system to improve the existing EOCR into a smart EOCR by adding the predictive maintenance function of the CLOUD environment. Firstly, the smart EOCR based motor system is introduced. Next, five state learning data sets collected from the motor system are constructed. After designing a state discriminator with DNN (Deep Neural Network), a widely used AI technique, and implementing it using the Python language. We prove the effectiveness of the state discriminator.\",\"PeriodicalId\":488820,\"journal\":{\"name\":\"Journal of The Korean Institute of Illuminating and Electrical Installation Engineers\",\"volume\":\"204 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of The Korean Institute of Illuminating and Electrical Installation Engineers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5207/jieie.2023.37.5.070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of The Korean Institute of Illuminating and Electrical Installation Engineers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5207/jieie.2023.37.5.070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI Based State Discriminator of Motor System for Smart EOCR
Recently, there has been growing interest in applying AI (artificial intelligence) technology to predict electric motor defect, perform prevention and maintenance, and reduce recovery costs and losses. This paper proposes an AI-based state discriminator for the electric motor system to improve the existing EOCR into a smart EOCR by adding the predictive maintenance function of the CLOUD environment. Firstly, the smart EOCR based motor system is introduced. Next, five state learning data sets collected from the motor system are constructed. After designing a state discriminator with DNN (Deep Neural Network), a widely used AI technique, and implementing it using the Python language. We prove the effectiveness of the state discriminator.