{"title":"On-line Monitoring of Capacitive Equipment Based on Big Data","authors":"Dongliang Wei, Zhi Wang, Jia Zhou, Jiangtian Chen","doi":"10.1145/3510858.3511392","DOIUrl":null,"url":null,"abstract":"With the development of the country in information technology, and those technology products are also used in life. Such as capacitive devices in power systems. But capacitive equipment will also have some failures, so it is necessary to monitor it online. Now researchers have found a lot of online monitoring methods, but in most of the current monitoring methods, the monitoring process will produce a huge amount of data, which is very large, so that technicians may miss some important data. In order to solve this problem which can not be discovered early because of the excessive amount of data, this paper adopts some methods based on big data to dig through the data the data obtained by the dig algorithm are statistically analyzed in big data technology. Using the data collected in this paper, through the analysis and research of these data, the results show that the application of big data technology to the on-line monitoring of capacitive equipment is very accurate and practical.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"28 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3510858.3511392","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the development of the country in information technology, and those technology products are also used in life. Such as capacitive devices in power systems. But capacitive equipment will also have some failures, so it is necessary to monitor it online. Now researchers have found a lot of online monitoring methods, but in most of the current monitoring methods, the monitoring process will produce a huge amount of data, which is very large, so that technicians may miss some important data. In order to solve this problem which can not be discovered early because of the excessive amount of data, this paper adopts some methods based on big data to dig through the data the data obtained by the dig algorithm are statistically analyzed in big data technology. Using the data collected in this paper, through the analysis and research of these data, the results show that the application of big data technology to the on-line monitoring of capacitive equipment is very accurate and practical.