{"title":"一种用于配电变压器诊断的智能多传感器","authors":"J. R. C. Faria, David M. C. Lima, F. Cardoso","doi":"10.1109/ICSENS.2018.8589667","DOIUrl":null,"url":null,"abstract":"The solution presented here addresses the condition monitoring and diagnosis of distribution transformers. An innovative autonomous multi-sensing unit is proposed, comprising a number of different sensors to supervise several critical variables associated with the transformer's operational performance. The combination and continuous study of these different elements enables predictive maintenance techniques, thus allowing a timely response to both trends and single events found in the apparatus under observation, which will decisively contribute to reduce outages and to improve the overall quality of service.","PeriodicalId":405874,"journal":{"name":"2018 IEEE SENSORS","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Smart Multi-Sensor for the Diagnosis of Distribution Transformers\",\"authors\":\"J. R. C. Faria, David M. C. Lima, F. Cardoso\",\"doi\":\"10.1109/ICSENS.2018.8589667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The solution presented here addresses the condition monitoring and diagnosis of distribution transformers. An innovative autonomous multi-sensing unit is proposed, comprising a number of different sensors to supervise several critical variables associated with the transformer's operational performance. The combination and continuous study of these different elements enables predictive maintenance techniques, thus allowing a timely response to both trends and single events found in the apparatus under observation, which will decisively contribute to reduce outages and to improve the overall quality of service.\",\"PeriodicalId\":405874,\"journal\":{\"name\":\"2018 IEEE SENSORS\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE SENSORS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSENS.2018.8589667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE SENSORS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENS.2018.8589667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Smart Multi-Sensor for the Diagnosis of Distribution Transformers
The solution presented here addresses the condition monitoring and diagnosis of distribution transformers. An innovative autonomous multi-sensing unit is proposed, comprising a number of different sensors to supervise several critical variables associated with the transformer's operational performance. The combination and continuous study of these different elements enables predictive maintenance techniques, thus allowing a timely response to both trends and single events found in the apparatus under observation, which will decisively contribute to reduce outages and to improve the overall quality of service.
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