{"title":"Inter phase fault detection in inverter fed induction motor using wavelet transform","authors":"B. A. Vinayak, Rahim Uddin, G. Jagadanaand","doi":"10.1109/CATCON.2017.8280193","DOIUrl":null,"url":null,"abstract":"In this research an inter-phase fault in the stator winding of Induction Motor will be analyzed by varying the switching frequency of the sine PWM inverter under different loading conditions. Induction Motor is modeled under faulty condition using mesh equations in matlab/simulink blocks. Stator current for different fault percentages in two phases are obtained by simulation. These current signals are further analyzed using wavelet coefficient and statistical parameters. The statistical parameter is used to develop a fault detection algorithm. The statistical data obtained is be used in Support Vector Machine (SVM) to develop a boundary equation. This equation will classify the healthy and faulty condition of motor.","PeriodicalId":250717,"journal":{"name":"2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CATCON.2017.8280193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this research an inter-phase fault in the stator winding of Induction Motor will be analyzed by varying the switching frequency of the sine PWM inverter under different loading conditions. Induction Motor is modeled under faulty condition using mesh equations in matlab/simulink blocks. Stator current for different fault percentages in two phases are obtained by simulation. These current signals are further analyzed using wavelet coefficient and statistical parameters. The statistical parameter is used to develop a fault detection algorithm. The statistical data obtained is be used in Support Vector Machine (SVM) to develop a boundary equation. This equation will classify the healthy and faulty condition of motor.