{"title":"Broken Rotor Bar Fault Diagnosis for Induction Motors Using Power Spectral Density and Complex Continuous Wavelet Transform Methods","authors":"Shafi Md. Kawsar Zaman, H. Marma, Xiaodong Liang","doi":"10.1109/CCECE.2019.8861517","DOIUrl":null,"url":null,"abstract":"Induction motors are widely used in various industrial sectors, fault diagnosis of induction motors are critical to prevent equipment failure and production downtime. In this paper, a stator current signature analysis method is proposed for squirrel cage induction motors’ broken rotor bar (BRB) fault diagnosis. Two different techniques are implemented: Power Spectral Density (PSD) based stator currents’ amplitude spectrum analysis; and one dimensional Complex Continuous Wavelet Transform (CWT) based stator currents’ time-scale spectrum analysis using Complex Morlet Wavelet (CMW). The performance of the two techniques are compared using experimental stator current data measured in a lab for a 0.25 HP induction motor. The stator current under healthy and faulty states of the motor were measured, the faults include one, two and three BRBs. For 2 and 3 BRB faults, the holes were drilled on the rotor bars 90 degree apart. Two loading conditions of the motor were used during the measurement, 30% and 85%. It is found that the CWT has better performance than the PSD estimates for the BRB fault detection.","PeriodicalId":352860,"journal":{"name":"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.2019.8861517","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Induction motors are widely used in various industrial sectors, fault diagnosis of induction motors are critical to prevent equipment failure and production downtime. In this paper, a stator current signature analysis method is proposed for squirrel cage induction motors’ broken rotor bar (BRB) fault diagnosis. Two different techniques are implemented: Power Spectral Density (PSD) based stator currents’ amplitude spectrum analysis; and one dimensional Complex Continuous Wavelet Transform (CWT) based stator currents’ time-scale spectrum analysis using Complex Morlet Wavelet (CMW). The performance of the two techniques are compared using experimental stator current data measured in a lab for a 0.25 HP induction motor. The stator current under healthy and faulty states of the motor were measured, the faults include one, two and three BRBs. For 2 and 3 BRB faults, the holes were drilled on the rotor bars 90 degree apart. Two loading conditions of the motor were used during the measurement, 30% and 85%. It is found that the CWT has better performance than the PSD estimates for the BRB fault detection.