{"title":"Effect of Unbalanced Voltage Supply Diagnosis Through Rotor Harmonics Signature and State Transitions","authors":"M. Sheikh, N. M. Nor, T. Ibrahim","doi":"10.1109/PECON.2016.7951621","DOIUrl":null,"url":null,"abstract":"Induction motor is a workhorse in industrial system and it poses a great challenge for the fault detection scheme due to large and complex data processing. Induction motor fault can lead to huge losses and excessive downtimes with regards to maintenance and production. An external fault like unbalanced voltages supply could be much severed and result in excessive losses, mechanical oscillations, over-voltage, and interference with control electronics. Detection of an abnormality like unbalanced voltage supply is a challenging task in the interaction of electrical motor and the power grid. In this paper, two new methods are presented to diagnose unbalanced voltage supply at the incipient stage. In first method, a new approach is introduced to formulate the total number of winding turns associated with a particular slot. After the formulation, the unbalanced voltage supply was diagnosed through rotor harmonics based on the formulation. While in the other method, the unbalanced asymmetry was detected through signal processing, symbolic time series analysis and D-Markov state transition. The proposed methods also distinguish motor operation under balanced and unbalanced voltage supply. In the proposed work, hardware setup was designed for experimental verification. For validation of the methods, experimental setup was designed to justify and distinguish the motor operating under balanced and unbalanced voltage supply.","PeriodicalId":259969,"journal":{"name":"2016 IEEE International Conference on Power and Energy (PECon)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Power and Energy (PECon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PECON.2016.7951621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Induction motor is a workhorse in industrial system and it poses a great challenge for the fault detection scheme due to large and complex data processing. Induction motor fault can lead to huge losses and excessive downtimes with regards to maintenance and production. An external fault like unbalanced voltages supply could be much severed and result in excessive losses, mechanical oscillations, over-voltage, and interference with control electronics. Detection of an abnormality like unbalanced voltage supply is a challenging task in the interaction of electrical motor and the power grid. In this paper, two new methods are presented to diagnose unbalanced voltage supply at the incipient stage. In first method, a new approach is introduced to formulate the total number of winding turns associated with a particular slot. After the formulation, the unbalanced voltage supply was diagnosed through rotor harmonics based on the formulation. While in the other method, the unbalanced asymmetry was detected through signal processing, symbolic time series analysis and D-Markov state transition. The proposed methods also distinguish motor operation under balanced and unbalanced voltage supply. In the proposed work, hardware setup was designed for experimental verification. For validation of the methods, experimental setup was designed to justify and distinguish the motor operating under balanced and unbalanced voltage supply.