Ramin Salehi Arashloo, Jose Luis Romeral Martinez, M. Salehifar
{"title":"A novel broken rotor bar fault detection method using park's transform and wavelet decomposition","authors":"Ramin Salehi Arashloo, Jose Luis Romeral Martinez, M. Salehifar","doi":"10.1109/DEMPED.2013.6645749","DOIUrl":null,"url":null,"abstract":"Detection of broken rotor bars has been an important but difficult work in fault diagnosis area of induction motors. The characteristic frequency components of faulted rotor are very close to the power frequency component but by far less in amplitude, which brings about great difficulty for accurate detection. In the present study, a new method is proposed in order to remove the main frequency component, resulting in more efficient detection of the rotor fault characteristics in the frequency spectrum of stator currents. The method is based on Park's transformation in combination with discrete wavelet decomposition to eliminate the effect of main frequency and zoom on the energy of objective fault related frequency components. In addition, the method efficiency is evaluated using Simulations in Matlab.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","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.2013.6645749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Detection of broken rotor bars has been an important but difficult work in fault diagnosis area of induction motors. The characteristic frequency components of faulted rotor are very close to the power frequency component but by far less in amplitude, which brings about great difficulty for accurate detection. In the present study, a new method is proposed in order to remove the main frequency component, resulting in more efficient detection of the rotor fault characteristics in the frequency spectrum of stator currents. The method is based on Park's transformation in combination with discrete wavelet decomposition to eliminate the effect of main frequency and zoom on the energy of objective fault related frequency components. In addition, the method efficiency is evaluated using Simulations in Matlab.