{"title":"大型感应电动机偏心故障指标综述","authors":"Iman Sadeghi, H. Ehya, J. Faiz","doi":"10.1109/PEDSTC.2017.7910347","DOIUrl":null,"url":null,"abstract":"This paper reviews eccentricity fault indices in large induction motors. The most advantageous features that have been widely used for eccentricity fault detection is introduced and impacts of load variations and power supply harmonics is also studied. Three different method based on thermal, vibration and electromagnetic field signal are presented and electrical signal chosen due to its non-invasive nature. Eccentricity is categorized into 6 groups and their competency are compared to each other.","PeriodicalId":414828,"journal":{"name":"2017 8th Power Electronics, Drive Systems & Technologies Conference (PEDSTC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Eccentricity fault indices in large induction motors an overview\",\"authors\":\"Iman Sadeghi, H. Ehya, J. Faiz\",\"doi\":\"10.1109/PEDSTC.2017.7910347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reviews eccentricity fault indices in large induction motors. The most advantageous features that have been widely used for eccentricity fault detection is introduced and impacts of load variations and power supply harmonics is also studied. Three different method based on thermal, vibration and electromagnetic field signal are presented and electrical signal chosen due to its non-invasive nature. Eccentricity is categorized into 6 groups and their competency are compared to each other.\",\"PeriodicalId\":414828,\"journal\":{\"name\":\"2017 8th Power Electronics, Drive Systems & Technologies Conference (PEDSTC)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 8th Power Electronics, Drive Systems & Technologies Conference (PEDSTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PEDSTC.2017.7910347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th Power Electronics, Drive Systems & Technologies Conference (PEDSTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PEDSTC.2017.7910347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Eccentricity fault indices in large induction motors an overview
This paper reviews eccentricity fault indices in large induction motors. The most advantageous features that have been widely used for eccentricity fault detection is introduced and impacts of load variations and power supply harmonics is also studied. Three different method based on thermal, vibration and electromagnetic field signal are presented and electrical signal chosen due to its non-invasive nature. Eccentricity is categorized into 6 groups and their competency are compared to each other.
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