Hari Kumar Raveendran Pillai, Mayadevi Nanappan, Mini Valiyakulam Prabhakaran, Shenil Pushpangadan Sathyabhama
{"title":"A Robust Technique for Detection, Diagnosis, and Localization of Switching Faults in Electric Drives Using Discrete Wavelet Transform","authors":"Hari Kumar Raveendran Pillai, Mayadevi Nanappan, Mini Valiyakulam Prabhakaran, Shenil Pushpangadan Sathyabhama","doi":"10.46604/ijeti.2023.10005","DOIUrl":null,"url":null,"abstract":"Detection, diagnosis, and localization of switching faults in electric drives are extremely important for operating a large number of induction motors in parallel. This study aims to present the design and development of switching fault detection, diagnosis, and localization strategy for the induction motor drive system (IMDS) by using a novel diagnostic variable that is derived from discrete wavelet transform (DWT) coefficients. The distinctiveness of the proposed algorithm is that it can identify single/multiple switch open and short faults and locate the defective switches using a single mathematical computation. The proposed algorithm is tested by simulation in MATLAB/Simulink and experimentally validated using the LabVIEW hardware-in-the-loop platform. The results demonstrate the robustness and effectiveness of the proposed technique in identifying and locating faults.","PeriodicalId":43808,"journal":{"name":"International Journal of Engineering and Technology Innovation","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering and Technology Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46604/ijeti.2023.10005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Detection, diagnosis, and localization of switching faults in electric drives are extremely important for operating a large number of induction motors in parallel. This study aims to present the design and development of switching fault detection, diagnosis, and localization strategy for the induction motor drive system (IMDS) by using a novel diagnostic variable that is derived from discrete wavelet transform (DWT) coefficients. The distinctiveness of the proposed algorithm is that it can identify single/multiple switch open and short faults and locate the defective switches using a single mathematical computation. The proposed algorithm is tested by simulation in MATLAB/Simulink and experimentally validated using the LabVIEW hardware-in-the-loop platform. The results demonstrate the robustness and effectiveness of the proposed technique in identifying and locating faults.
期刊介绍:
The IJETI journal focus on the field of engineering and technology Innovation. And it publishes original papers including but not limited to the following fields: Automation Engineering Civil Engineering Control Engineering Electric Engineering Electronic Engineering Green Technology Information Engineering Mechanical Engineering Material Engineering Mechatronics and Robotics Engineering Nanotechnology Optic Engineering Sport Science and Technology Innovation Management Other Engineering and Technology Related Topics.