Muhammad Sarfraz Moiz, Shazaib Shamim, M. Abdullah, Hamdan Khan, I. Hussain, Anas Bin Iftikhar, T. Memon
{"title":"基于电流和振动特征分析的三相感应电动机健康监测","authors":"Muhammad Sarfraz Moiz, Shazaib Shamim, M. Abdullah, Hamdan Khan, I. Hussain, Anas Bin Iftikhar, T. Memon","doi":"10.1109/ICRAI47710.2019.8967356","DOIUrl":null,"url":null,"abstract":"This paper revolves around the discussion of detection of faults occurs in three-phase induction motor especially outer-race bearing faults using two significant methods, Current Signature Analysis and Vibration Signature Analysis, in order to deploy predictive maintenance technique. Detection of bearing fault is important because most of the failures in induction motors are related to bearing faults which can lead to excessive downtimes and large revenue losses. Early detection of fault helps to reduce downtime and unexpected breakdowns. The current signature analysis uses stator currents spectrum to determine fault harmonics around the fundamental frequency. Every machine generates vibration and due to dynamic stresses, vibrational behavior of the machine is influenced by the mechanical condition. This disturbance can be analyzed by Vibration signature analysis. The experiment is done on induction motor of 1 HP, connected to three-phase 50 Hz supply and 6303 model bearings are artificially damaged to generate fault conditions. From experimental results, we have compared the above two techniques for fault detection and analyze the bearing fault frequency.","PeriodicalId":429384,"journal":{"name":"2019 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Health Monitoring of Three-Phase Induction Motor Using Current and Vibration Signature Analysis\",\"authors\":\"Muhammad Sarfraz Moiz, Shazaib Shamim, M. Abdullah, Hamdan Khan, I. Hussain, Anas Bin Iftikhar, T. Memon\",\"doi\":\"10.1109/ICRAI47710.2019.8967356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper revolves around the discussion of detection of faults occurs in three-phase induction motor especially outer-race bearing faults using two significant methods, Current Signature Analysis and Vibration Signature Analysis, in order to deploy predictive maintenance technique. Detection of bearing fault is important because most of the failures in induction motors are related to bearing faults which can lead to excessive downtimes and large revenue losses. Early detection of fault helps to reduce downtime and unexpected breakdowns. The current signature analysis uses stator currents spectrum to determine fault harmonics around the fundamental frequency. Every machine generates vibration and due to dynamic stresses, vibrational behavior of the machine is influenced by the mechanical condition. This disturbance can be analyzed by Vibration signature analysis. The experiment is done on induction motor of 1 HP, connected to three-phase 50 Hz supply and 6303 model bearings are artificially damaged to generate fault conditions. From experimental results, we have compared the above two techniques for fault detection and analyze the bearing fault frequency.\",\"PeriodicalId\":429384,\"journal\":{\"name\":\"2019 International Conference on Robotics and Automation in Industry (ICRAI)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Robotics and Automation in Industry (ICRAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAI47710.2019.8967356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Robotics and Automation in Industry (ICRAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAI47710.2019.8967356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Health Monitoring of Three-Phase Induction Motor Using Current and Vibration Signature Analysis
This paper revolves around the discussion of detection of faults occurs in three-phase induction motor especially outer-race bearing faults using two significant methods, Current Signature Analysis and Vibration Signature Analysis, in order to deploy predictive maintenance technique. Detection of bearing fault is important because most of the failures in induction motors are related to bearing faults which can lead to excessive downtimes and large revenue losses. Early detection of fault helps to reduce downtime and unexpected breakdowns. The current signature analysis uses stator currents spectrum to determine fault harmonics around the fundamental frequency. Every machine generates vibration and due to dynamic stresses, vibrational behavior of the machine is influenced by the mechanical condition. This disturbance can be analyzed by Vibration signature analysis. The experiment is done on induction motor of 1 HP, connected to three-phase 50 Hz supply and 6303 model bearings are artificially damaged to generate fault conditions. From experimental results, we have compared the above two techniques for fault detection and analyze the bearing fault frequency.