P. J. Broniera, W. S. Gongora, A. Goedtel, W. Godoy
{"title":"应用人工神经网络诊断三相异步电动机定子绕组匝间短路","authors":"P. J. Broniera, W. S. Gongora, A. Goedtel, W. Godoy","doi":"10.1109/DEMPED.2013.6645729","DOIUrl":null,"url":null,"abstract":"The application of induction motors in industry is widespread. Thus, several studies have presented strategies for the diagnosis and prediction of failures in these motors. One technique used is based on the recent utilization of intelligent systems for detecting faults in electric motors. Thus, this paper proposes an alternative tool to traditional techniques for fault detection of a short circuit between the inter-turns of the stator winding using artificial neural networks to analyze stator current signals in the time domain. Experimental results are presented to validate the proposed approach.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Diagnosis of stator winding inter-turn short circuit in three-phase induction motors by using artificial neural networks\",\"authors\":\"P. J. Broniera, W. S. Gongora, A. Goedtel, W. Godoy\",\"doi\":\"10.1109/DEMPED.2013.6645729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of induction motors in industry is widespread. Thus, several studies have presented strategies for the diagnosis and prediction of failures in these motors. One technique used is based on the recent utilization of intelligent systems for detecting faults in electric motors. Thus, this paper proposes an alternative tool to traditional techniques for fault detection of a short circuit between the inter-turns of the stator winding using artificial neural networks to analyze stator current signals in the time domain. Experimental results are presented to validate the proposed approach.\",\"PeriodicalId\":425644,\"journal\":{\"name\":\"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEMPED.2013.6645729\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEMPED.2013.6645729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Diagnosis of stator winding inter-turn short circuit in three-phase induction motors by using artificial neural networks
The application of induction motors in industry is widespread. Thus, several studies have presented strategies for the diagnosis and prediction of failures in these motors. One technique used is based on the recent utilization of intelligent systems for detecting faults in electric motors. Thus, this paper proposes an alternative tool to traditional techniques for fault detection of a short circuit between the inter-turns of the stator winding using artificial neural networks to analyze stator current signals in the time domain. Experimental results are presented to validate the proposed approach.