{"title":"基于循环迭代算法的电表故障分离","authors":"Xiaokang Liu, Yuexian Hou, Shengnan Zhang","doi":"10.1109/IICSPI.2018.8690394","DOIUrl":null,"url":null,"abstract":"The growing amount of fault smart meter raises concern from the State Grid Corporation of China in Tianjin. However, data analysis on smart meter fault is still not enough. This paper investigates the fault causes among fault meters data and tries to separate the effective meter fault causes out. To this end, several steps have been followed: first, it builds a fault causes analysis system to find out the effective causes. Second, it raises a cause separation method to extract effective reasons from massive causes. Then a cyclic iterative algorithm has been proposed by maximum likelihood solution for solving meter fault causes equations built in cause separation method. The cause separation method behaves better in practical applications than in the traditional statistics approach. The methods are applied to and evaluated on the practical data.","PeriodicalId":6673,"journal":{"name":"2018 IEEE International Conference of Safety Produce Informatization (IICSPI)","volume":"81 1","pages":"188-191"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Meter Fault Causes Separation Based on Cyclic Iterative Algorithm\",\"authors\":\"Xiaokang Liu, Yuexian Hou, Shengnan Zhang\",\"doi\":\"10.1109/IICSPI.2018.8690394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The growing amount of fault smart meter raises concern from the State Grid Corporation of China in Tianjin. However, data analysis on smart meter fault is still not enough. This paper investigates the fault causes among fault meters data and tries to separate the effective meter fault causes out. To this end, several steps have been followed: first, it builds a fault causes analysis system to find out the effective causes. Second, it raises a cause separation method to extract effective reasons from massive causes. Then a cyclic iterative algorithm has been proposed by maximum likelihood solution for solving meter fault causes equations built in cause separation method. The cause separation method behaves better in practical applications than in the traditional statistics approach. The methods are applied to and evaluated on the practical data.\",\"PeriodicalId\":6673,\"journal\":{\"name\":\"2018 IEEE International Conference of Safety Produce Informatization (IICSPI)\",\"volume\":\"81 1\",\"pages\":\"188-191\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference of Safety Produce Informatization (IICSPI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IICSPI.2018.8690394\",\"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 International Conference of Safety Produce Informatization (IICSPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IICSPI.2018.8690394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Meter Fault Causes Separation Based on Cyclic Iterative Algorithm
The growing amount of fault smart meter raises concern from the State Grid Corporation of China in Tianjin. However, data analysis on smart meter fault is still not enough. This paper investigates the fault causes among fault meters data and tries to separate the effective meter fault causes out. To this end, several steps have been followed: first, it builds a fault causes analysis system to find out the effective causes. Second, it raises a cause separation method to extract effective reasons from massive causes. Then a cyclic iterative algorithm has been proposed by maximum likelihood solution for solving meter fault causes equations built in cause separation method. The cause separation method behaves better in practical applications than in the traditional statistics approach. The methods are applied to and evaluated on the practical data.