{"title":"以局部放电测量为例的大数据集处理与分析","authors":"Johannes Drechsel, Henry Barth, L. Rebenklau","doi":"10.1109/ISSE54558.2022.9812784","DOIUrl":null,"url":null,"abstract":"As is the case in an increasing number of technical fields, large amounts of raw data are recorded during partial discharge (PD) measurements. This paper shows both common techniques and PD measurement-specific methods of data analysis. Defined test specimens are specifically designed, manufactured, and measured in order to provide raw data. Different organisation, calculation, and visualization options are evaluated regarding their applicability for finding correlations between measurement data and substrate parameters. Dependencies between partial discharge parameters and the specific test substrates’ properties are made visible.","PeriodicalId":413385,"journal":{"name":"2022 45th International Spring Seminar on Electronics Technology (ISSE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Handling and Analysis of Large Datasets Using the Example of Partial Discharge Measurement\",\"authors\":\"Johannes Drechsel, Henry Barth, L. Rebenklau\",\"doi\":\"10.1109/ISSE54558.2022.9812784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As is the case in an increasing number of technical fields, large amounts of raw data are recorded during partial discharge (PD) measurements. This paper shows both common techniques and PD measurement-specific methods of data analysis. Defined test specimens are specifically designed, manufactured, and measured in order to provide raw data. Different organisation, calculation, and visualization options are evaluated regarding their applicability for finding correlations between measurement data and substrate parameters. Dependencies between partial discharge parameters and the specific test substrates’ properties are made visible.\",\"PeriodicalId\":413385,\"journal\":{\"name\":\"2022 45th International Spring Seminar on Electronics Technology (ISSE)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 45th International Spring Seminar on Electronics Technology (ISSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSE54558.2022.9812784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 45th International Spring Seminar on Electronics Technology (ISSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSE54558.2022.9812784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Handling and Analysis of Large Datasets Using the Example of Partial Discharge Measurement
As is the case in an increasing number of technical fields, large amounts of raw data are recorded during partial discharge (PD) measurements. This paper shows both common techniques and PD measurement-specific methods of data analysis. Defined test specimens are specifically designed, manufactured, and measured in order to provide raw data. Different organisation, calculation, and visualization options are evaluated regarding their applicability for finding correlations between measurement data and substrate parameters. Dependencies between partial discharge parameters and the specific test substrates’ properties are made visible.