{"title":"基于振动的电力变压器机械故障模式鲁棒健康诊断","authors":"J. Yoon, B. Youn, K. Park, Wook-ryun Lee","doi":"10.1109/ICPHM.2013.6621421","DOIUrl":null,"url":null,"abstract":"A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers.","PeriodicalId":178906,"journal":{"name":"2013 IEEE Conference on Prognostics and Health Management (PHM)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Vibration-based robust health diagnostics for mechanical failure modes of power transformers\",\"authors\":\"J. Yoon, B. Youn, K. Park, Wook-ryun Lee\",\"doi\":\"10.1109/ICPHM.2013.6621421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers.\",\"PeriodicalId\":178906,\"journal\":{\"name\":\"2013 IEEE Conference on Prognostics and Health Management (PHM)\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Conference on Prognostics and Health Management (PHM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPHM.2013.6621421\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Conference on Prognostics and Health Management (PHM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPHM.2013.6621421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vibration-based robust health diagnostics for mechanical failure modes of power transformers
A power transformer is one of the main components in a power plant and transformer failure may provoke power plant shut-down with significant capital loss. Many techniques of vibration-based health diagnostics have been developed in order to prevent mechanical failures of the transformer. Vibration-based health diagnostics results are generally sensitive to the number of sensors and their locations. This study aims at developing robust health diagnostics for two dominant mechanical failure mechanisms of the transformer. Based upon the characteristics of transformer vibration, robust health indices were developed using sensitivity analysis. This study employed 33 transformers and each with 36~48 accelerometers for demonstration purpose. It is concluded that the proposed health index are suitable for robust health diagnostics and fault identification of power transformers.