{"title":"基于人工神经网络的输电线路故障方向估计","authors":"M. Sanaye-Pasand, O. Malik","doi":"10.1109/CCECE.1996.548263","DOIUrl":null,"url":null,"abstract":"The direction of a fault on a power transmission line needs to be identified rapidly and correctly. To classify forward and backward faults on a given line, a neural network's abilities in pattern recognition and classification could be considered as a solution. To demonstrate the applicability of this solution, a neural network technique is employed to design two different fault direction estimators. Details of the design procedure and results of performance studies with the proposed networks are given and compared.","PeriodicalId":269440,"journal":{"name":"Proceedings of 1996 Canadian Conference on Electrical and Computer Engineering","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Power transmission lines fault direction estimation using artificial neural networks\",\"authors\":\"M. Sanaye-Pasand, O. Malik\",\"doi\":\"10.1109/CCECE.1996.548263\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The direction of a fault on a power transmission line needs to be identified rapidly and correctly. To classify forward and backward faults on a given line, a neural network's abilities in pattern recognition and classification could be considered as a solution. To demonstrate the applicability of this solution, a neural network technique is employed to design two different fault direction estimators. Details of the design procedure and results of performance studies with the proposed networks are given and compared.\",\"PeriodicalId\":269440,\"journal\":{\"name\":\"Proceedings of 1996 Canadian Conference on Electrical and Computer Engineering\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1996 Canadian Conference on Electrical and Computer Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE.1996.548263\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1996 Canadian Conference on Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.1996.548263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Power transmission lines fault direction estimation using artificial neural networks
The direction of a fault on a power transmission line needs to be identified rapidly and correctly. To classify forward and backward faults on a given line, a neural network's abilities in pattern recognition and classification could be considered as a solution. To demonstrate the applicability of this solution, a neural network technique is employed to design two different fault direction estimators. Details of the design procedure and results of performance studies with the proposed networks are given and compared.