O. Moldovan, R. Ghincu, Alin Octavian Moldovan, D. Noje, R. Ţarcă
{"title":"基于数据采集和神经网络数据处理的三相异步电动机故障检测","authors":"O. Moldovan, R. Ghincu, Alin Octavian Moldovan, D. Noje, R. Ţarcă","doi":"10.15837/ijccc.2022.3.4788","DOIUrl":null,"url":null,"abstract":"The main objective of this paper is to investigate how a failure in the functioning of a normal electrical system represented by a three-phase asynchronous motor will modify the voltages and currents present in the system and if it is possible to design a system that is able to automatically detect the fault, based on the use of modern data acquisition system and powerful computer processing capabilities. The detection of faulty signals is realised using Feedforward Artificial Neural Networks.","PeriodicalId":179619,"journal":{"name":"Int. J. Comput. Commun. Control","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Fault Detection in Three-phase Induction Motor based on Data Acquisition and ANN based Data Processing\",\"authors\":\"O. Moldovan, R. Ghincu, Alin Octavian Moldovan, D. Noje, R. Ţarcă\",\"doi\":\"10.15837/ijccc.2022.3.4788\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main objective of this paper is to investigate how a failure in the functioning of a normal electrical system represented by a three-phase asynchronous motor will modify the voltages and currents present in the system and if it is possible to design a system that is able to automatically detect the fault, based on the use of modern data acquisition system and powerful computer processing capabilities. The detection of faulty signals is realised using Feedforward Artificial Neural Networks.\",\"PeriodicalId\":179619,\"journal\":{\"name\":\"Int. J. Comput. Commun. Control\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Commun. Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15837/ijccc.2022.3.4788\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Commun. Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15837/ijccc.2022.3.4788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault Detection in Three-phase Induction Motor based on Data Acquisition and ANN based Data Processing
The main objective of this paper is to investigate how a failure in the functioning of a normal electrical system represented by a three-phase asynchronous motor will modify the voltages and currents present in the system and if it is possible to design a system that is able to automatically detect the fault, based on the use of modern data acquisition system and powerful computer processing capabilities. The detection of faulty signals is realised using Feedforward Artificial Neural Networks.
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