I. Tsoumas, G. Georgoulas, A. Safacas, G. Vachtsevanos
{"title":"Empirical Mode Decomposition of the stator start-up current for rotor fault diagnosis in asynchronous machines","authors":"I. Tsoumas, G. Georgoulas, A. Safacas, G. Vachtsevanos","doi":"10.1109/ICELMACH.2008.4799987","DOIUrl":null,"url":null,"abstract":"This paper investigates a novel approach for rotor fault diagnosis in asynchronous machines. Empirical mode decomposition (EMD) is applied to the measured start-up current. More specifically, the space vector of the stator start-up current is decomposed into complex intrinsic mode functions (IMFs) in order to analyze the asynchronous machine's transient. It is shown that in the case of rotor fault a particular IMF arises which characterizes the presence of the fault. The instantaneous frequency and the amplitude of the IMF can be used for an efficient fault diagnosis.","PeriodicalId":416125,"journal":{"name":"2008 18th International Conference on Electrical Machines","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 18th International Conference on Electrical Machines","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICELMACH.2008.4799987","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper investigates a novel approach for rotor fault diagnosis in asynchronous machines. Empirical mode decomposition (EMD) is applied to the measured start-up current. More specifically, the space vector of the stator start-up current is decomposed into complex intrinsic mode functions (IMFs) in order to analyze the asynchronous machine's transient. It is shown that in the case of rotor fault a particular IMF arises which characterizes the presence of the fault. The instantaneous frequency and the amplitude of the IMF can be used for an efficient fault diagnosis.